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Dana Gardner is president and principal analyst at Interarbor Solutions (www.interarbor-solutions.com), an enterprise IT analysis, market research, and consulting firm. Gardner, a leading identifier of software productivity trends and new IT business growth opportunities, honed his skills and... More
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  • Top 25 SharePoint Influencers: Social Influence Nicely Collides With Collaboration Clouds

    Educating technology markets and communities is now, more than ever, a function of influence, social media, digital word of mouth -- and of cultivating an ecosystem of trusted collaboration. The role of social media and the power of personal connections have really become dominant forces in how people learn how to find and use technology.

    This is such a major departure from the past - marketing has changed more in the last 5 years than the previous 50 - that any instruction on what actually works best these days is highly prized.

    Therefore, I've been keenly interested in how the hottest new wave of marketing - digital social influence -- intersects with one the hottest areas of cloud computing - software-as-a-service (SaaS) collaboration and documents/objects sharing.

    Do these new waves double-up, cancel out, create an interference pattern, or harmonize in new and valuable ways? I really want to know.

    So I helped guide the creation of a list of the top 25 U.S. SharePoint influencers, recently unveiled at the recent SharePoint 2014 Conference in Las Vegas. The effort was sponsored by harmon.ie, the provider of a collaboration app for a single-screen, seamless user experience anytime, anywhere, and on any device. Here's the full list.

    I'll be doing a BriefingsDirect podcast soon with a panel of these newly identified influencers on SharePoint challenges and opportunities to help find out what matters most in the SharePoint ecosystem.

    I've been an avid observer of Microsoft for more than 20 years. At one time, there was no better company in all of IT at marketing and evangelizing into multiple user bases: developers, channel, independent software vendors (ISVs), end users, and enterprises.

    But what about now, given that the evangelizing game has changed so much? Can Microsoft, which itself is undergoing wrenching transitions, be as good at the new marketing ways as in the past? Again, I really want to know.

    Tip of the arrow

    Industry influencers are the tip on the arrow of how social media can be a positive force for sharing knowledge - whether it's on Twitter or blogs or at events. With influencers, I benefit from them and they benefit from me. This is the same for anyone engaged in social media. So it's really a powerful way to learn and to then add something to that learning process to then make it almost a hive-mentality or ecosystem-mentality affair.

    It's no surprise that of the top 25 SharePoint influencers that we identified, 48 percent are SharePoint specialists or consultants. The other two major categories are senior executives and SharePoint architects/engineers/developers. And gender equality had a good year, as the growth in women SharePoint influencers over the previous year -- up to 4 spots and 16 percent of the list -- marks a significant rise over only 1 female influencer on the 2013 list.

    It's the people in the know, in the technology trenches, that see both the forest and trees that can then effectively influence the way markets learn.

    So I am very bullish on the role of influencers as a spark or catalyst for larger social interactions and for new wave knowledge transfer. Those social interactions in a discrete community like the SharePoint ecosystem are a big part of what drives innovation, and can help users as well as supplier companies understand the best course for products and services.

    Of course, the role of SharePoint, Yammer, and Office 365 is rapidly shifting into more of a cloud-collaboration, hive offering itself. So how apropos for it to use social influence to evangelize tools that consequently promote social influence and knowledge sharing?

    You have to remember that SharePoint, once likened to a corporate intranet, is extending into a cloud platform with SharePoint 2013. It's far more integratable. And, there are rich features for security and versioning of file data. Exchange is also becoming predominately cloud-oriented in its new function drive.

    Boundaries blurring

    The boundaries then between all these Microsoft communications "products" are blurring because they are increasingly bundles of cloud data services.

    Marketing products is so 1990s. Letting the social-hive support a fast-evolving hive of cloud-based collaboration services is so now. That's why Microsoft must become adept at social and must properly influence the influencers. There's no better way to scale down its cloud services - SharePoint and Office 365 chief among them. Single office/home office (SOHO) and small- and medium-sized businesses (SMBs) are where these services should grow like crazy, especially for those used to working with Exchange, Outlook, and Office. They will be guided by their chosen social milieu and peers, not by Microsoft's spec sheets and sales force.

    So check out the list of top SharePoint influencers, and also consider how the role of influencers is not so much outsized as right-sized. As companies and workers seek better collaboration and coordination among themselves, they will look to among themselves for the best means. SharePoint needs to be this chosen common controlled hive for employees, especially through the mobile tier.

    And look for our BriefingsDirect podcast soon with a panel of these latest influencers. Many are returning because this is the third consecutive annual list of SharePoint influencers.

    It seems to me that the voice of the community, whether it's around a product or service or an industry or a vertical market, should be really important to vendors like Microsoft. They should be, I think, pretty sensitive to learning from the community, and I hope the community takes the opportunity to voice its opinion and make its requirements known as these companies produce new products and adjusts their strategies.

    But this is a time where change is ripe, and Microsoft is in a position to react in a way that only benefits the users. The influencers can certainly show them how.

    You may also be interested in:
    Mar 17 1:13 PM | Link | Comment!
  • HP HAVEn CTO Mundada On New Ways For Businesses To Gain Transformation From Big Data And New Wave Analysis

    Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

    Big data capabilities and advanced business analytics have now become essential to nearly any business development activity.

    The benefits that enterprises can get if they can get their hands around big data analytics and apply it to business challenges are quickly being documented -- and they come as big new profits and major market advantages. Industries around the world are rapidly seeking transformational projects using big data to gain competitive advantage.

    As part of the next edition of the HP Big Data Podcast Series, BriefingsDirect sat down with two HP executives to learn how these advanced analytics seekers can best accomplish their goals. The insights gleaned include how companies worldwide are best capturing myriad knowledge, gaining ever deeper analysis, and rapidly and securely making those insights available to more people on their own terms.

    So join this executive-level discussion highlighting how the latest version of HP HAVEn produces new business analytics value and strategic return with Girish Mundada, Chief Technology Officer for HP HAVEn, and Dan Wood, Worldwide Solution Marketing Lead for Big Data at HP Software. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

    Here are some excerpts:

    Gardner: We're in a fascinating time because analytics and big data are now top of mind. What was once relegated to a fairly small group of data scientists and analysts as reporting tools -- and I am thinking about business intelligence (BI) -- has really now become a comprehensive capability that's proving essential to nearly any business strategy.

    What's behind this eagerness to gain big-data capabilities and exploit analytics so broadly?

    Wood: We're starting to see some very clear quantification of the value and the benefits of big data. It's fair to say that big data is probably the hottest topic in the industry.

    Wood

    There's a lot of talk across all forms of media about big data right now, but what's happened is that credible publications like the "Harvard Business Review," for example, have started to put solid numbers around the benefits that enterprises can get if they can get their hands around big-data analytics and apply it to business challenges.

    For example, Harvard Business Review is saying that, on average, data-driven organizations will be five percent more productive and six percent more profitable than their competitors.

    Worth chasing after

    Think about that. A six-percent distinct profitability increase would double the stock price for a lot of organizations. So there really is a prize worth chasing after.

    What we're seeing, Dana, is much more widespread interest across the organization and not just within IT. We're seeing line-of-business leaders understanding and, in many organizations, actually starting to benefit from big-data analytics.

    They're able to analyze the call logs in a call center, better understand the clickstreams on a website, and better understand how customers are using products. All of these are ways of analyzing large amounts of data and directly tying it to specific line-of-business problems.

    That's where we are right now. Industries around the world are going through transformational projects using big data to gain competitive advantage.

    Gardner: It's interesting too, Dan, that they're not just taking these as individual data sets and handling them individually, but increasingly businesses are combining them, and finding new relationships, and doing things that they really couldn't have done before.

    Wood: Absolutely. It's the idea of 360-degree view of their internal operations, or of their external customer trends and needs -- and it's come from combining data sets.

    For example, they're combining social media analytics on customers with the call logs into the call center, with internal systems of record around the customer relationship management (CRM) and ongoing customer transactions. It's by combining all those insights that the real big-data opportunity reveals itself.

    Gardner: And the sources for those insights and data, of course, are across almost any type of information asset. It's not a just structured data or data that your application standard is around -- it's getting all the data all of the time.

    Wood: That's right. In some ways, this industry label of big data is perhaps not the most helpful, because it's not just the volume of data that is the challenge and the opportunity for the business. It's the variety of sources, as you've alluded to, and also the velocity at which that data is moving.

    The business needs to get hold of these multiple sources of data and immediately be able to apply the analytics, get the insights, and make the business decisions. This is why still the vast majority of that data that's available to an enterprise remains dark.

    Unused and unexploited

    It's unused and unexploited. Organizations, with their traditional analytics systems, are struggling to get the meaning and insights from all these data types that we mentioned. These include unstructured information, such as social media sentiment, voice recordings, potentially even video recordings, and the structured and semi-structured things like log files and data center data. For many organizations, getting the information quickly enough out of their CRM and enterprise resource planning (ERP) systems is a challenge as well.

    Gardner: So we see that there's a great desire to do this, and there are great returns on being able to do this well. We talked about some of the general challenges. What specifically is holding people up?

    Is this an issue of cost, complexity, or skills? Why aren't companies able to move beyond this small fraction of the available information to which they could be applying such important insight and analytics?

    Wood: It's a complexity and a skills challenge, as you mentioned. The systems they have today, Dana, typically aren't set up to able to analyze these vast amounts of unstructured information, and also to be able to analyze the structured data at a speed needed by the organization.

    Think about the need to analyze immediately a clickstream from an online shopping application or a pay-to-use application that an organization has. That is, a rapid-scale analysis of a large amount of structured data. Typically, the analytic systems that organizations have had aren't able to cope with that or with the unstructured human information.

    This is why HP has created the HAVEn Big Data Platform, and Girish will talk in more detail about this, and how it brings together the analytics engine needed to address these issues.

    Just as importantly, there's the ecosystem around HAVEn, which includes HP experts and services and services from partners, to bring together the skills needed to turn this data collection into useful information.

    And there are skills around data scientists, as well -- skills around understanding the right questions the line of business needs to be asking, and understanding actually how to visualize and represent the data.

    Gardner: What were the guiding principles that you were thinking of when HAVEn was being put together?

    Talking to customers

    Mundada: HAVEn came together not by creating it in a dark room somewhere in the back office. It came together by talking to customers. On a regular basis, I meet with some of HP's largest customers worldwide, getting input from them. And they're telling us what their current problems are.

    Mundada

    Let me see if I can describe the landscape in a typical organization, and we can go from there. You'll see why we created HAVEn.

    Let's visualize four different waves of data. Back in early '60s,'70s, even part of the '80s, mainframes were the primary way to process data, and we used them for operationalizing certain parts of data processing, where data was extremely high-value. If you look at the cost of the systems, it was phenomenal.

    Then came the next wave in the '80s, where we went into what I call client-server computing, and we already know several companies that were created in this space.

    I've lived in Silicon Valley for almost 30 years now, and a whole bunch of new companies were born in this space. I worked for a company, Postgres, which became Illustra, then became Informix, and became IBM. If you look at that entire wave of OLTP technologies, we created data-processing technologies designed to solve basic business problems.

    Application software was created: CRM, supplier relationship management (SRM), you name it. Many companies that did consulting around that were created, too. That was that second wave after the mainframe.

    Then came the third wave, where we took this data from all these transactional systems, brought them together to find out some basic analysis, which we now call business analytics, to find out "who is my most profitable customer, what are they buying, why are they buying," and things of that nature.

    We created companies for that wave, too, and many technologies. Exadata, Teradata, Netezza, and a whole bunch of companies and applications were born in that space. That wave lasted for quite a while.

    What we're seeing now is that from 2003 onward, something very fundamental has happened. At least, that's the way I've been seeing this. If you look at the three Vs that Dan has described -- volume, velocity, and variety -- we're talking about volumes that are growing exponentially. In the past, they were growing linearly. That creates a very different kind of requirement.

    More importantly, if you look at the variety that Dan mentioned, that's really the key driver in my mind. People are now routinely bringing in machine data, human data, and your traditional structured warehouses -- all of them together.

    If you visualize a bar graph, you would see that 10 percent of the data that we now can monetize is coming from traditional sources, whereas 90 percent of the data that we need to monetize is now sitting in machine data and human data.

    High velocity analytics

    What we're trying to do with HAVEn is create a combined platform, where you can combine these three different data types and do very high-velocity analytics.

    As a simple example, if you look at Apache Web Server logs, that data is used historically by the security people to see if anybody is breaking in. That data was being used by operational people to see if machines aren't overloaded.

    More importantly the digital marketing guys now want to look at that data to see who's coming to their website, what they're buying, what they're not buying, why they're buying, and which geographies they're coming from. Then, they want to combine all these data sets with their existing structured data to make sense out of it.

    Today, it's a mess in the market. When we talk to our partners and customers, they're saying that they have point solutions for each of these things, and if you want to combine that data, it's really hard. That's why we had to create HAVEn.

    HAVEn is the fourth wave. HAVEn is specifically about big data, the fourth wave. If you look at HP's portfolio, we sell products and services across each of these waves, and the fastest growing wave right now is the big-data wave. It's growing at about 35 percent a year, according to Gartner, and that's why we're excited about it.

    Gardner: Now we know why you created it and what it's supposed to do. Tell us a little bit more about what's included in HAVEn and why it is that you've been able combine product and platform to solve this very difficult task.

    Mundada: If you look at what's required now to process big data in its entirety, one product no longer can do it all. There is a very famous paper written by some university professors titled "One size does not fit all." It proves that different data structures are able to solve different kinds of data problems far more efficiently.

    One way to think about big data is to think of it as a pile of dirt. It's a big pile. In that pile, there's gold, silver, platinum, iron, and other metals you don't even know. If the cost of mining that data is high, obviously you're going to go after only the platinum and some known objects that you care about, because that's all you can afford.

    HAVEn is about bringing that cost of processing down to a very, very low level so you can go after more metals. That means you have to bring together a set of technologies to be able to solve this. If you look at the last three years, HP has made very significant amounts of investments in the big-data space.

    Best of breed

    We bought companies that were best of breed to try to solve specific problems. We bought Autonomy, Vertica, ArcSight, Fortify, TippingPoint, 3PAR Data, and Knightsbridge.

    Now, we have a set of technologies to be able to combine them into a unique experience. Think of it almost like Microsoft Office. Before you had Microsoft Office, you would buy a word processor from one company, a spreadsheet from another company, and presentation software from a third company.

    Let's say you wanted to create a simple table. If you had created it in a word processor or even a spreadsheet, you couldn't mix and match that. It was impossible to mix and match very different types.

    Then, Microsoft came to the table and said, "Look, here's a simplified solution." If you want to create a table, go ahead and create it in PowerPoint. Or if you want to create more complicated thing, put it in Excel. Then, take that Excel and put it in PowerPoint. Or, you can put the whole thing into a Word document. That was the beauty of what Microsoft did.

    We're trying to do something similar for big data, make it very easy for people to combine all these different engines and the different data types and write simple applications on it.

    Gardner: What beyond the products and binding them together makes HAVEn unique?

    Mundada: HAVEn is really two different concepts. There's the HAVEn data platform, which we'll talk about now, and there's a HAVEn ecosystem, which I'll mention in a minute.

    HAVEn means Hadoop, Autonomy, Vertica, Enterprise Security, and "n" applications. That's the acronym. So let's look at one of these pieces, and why we need an architecture like this.

    As I said, today you need to combine different sets of data techniques to solve different problems, and they have to work seamlessly. That's what we did with HAVEn. I've been with HAVEn from day zero, before the project concept started, and I can tell you why and how we added these pieces and how we're trying to integrate them better.

    If you look at Hadoop as an ecosystem part of that HAVEn, our story with Hadoop at HP is that Hadoop is an integral part of HAVEn. We see a lot of our customers and partners betting on Hadoop and we think it's a good thing to keep Hadoop open and non-proprietary.

    Leading vendors

    We also today work with all leading Hadoop vendors, so we have shipping appliances as well as reference architectures for both Cloudera and Hortonworks, and we're working now with MapR to create similar infrastructure. That's our Hadoop's story.

    We've also found that our customers are saying they want some flexibility in Hadoop. Today, they may want one vendor, and tomorrow, they may decide to go to another vendor for whatever business reasons they choose. They want to know if we can provide a simple management tool that works across multiple Hadoop distributions.

    As an example, we had to extend our Business Service Management (BSM) portfolio, so we can manage Hadoop, Vertica, hardware, storage, and networking all from within one environment. This is simply operationalizing it. Having a standardized set of hardware that matches multiple Hadoop distributions was another thing we had to do. There are many such enterprise-class innovations that you'll see coming from HP.

    But more than that, we also found that Hadoop is really good for certain kinds of applications today, and obviously, the community will extend that. You will see more and more innovations coming from that community and ecosystem.

    Today, there are several areas where there are holes in Hadoop, or maybe they're not as strong as commercial products. One such area that you see is SQL. The SQL phase of Hadoop is going to be one of the key differentiators across the different Hadoop packaging.

    In that area, we have a technology called Vertica, which is the V part of HAVEn, and you'll see companies like Facebook, using a combination of both Hadoop and Vertica.

    The classic use case we see is that people will bring all kinds of raw data, put it into Hadoop, and do some batch processing there. Hadoop is great as a file system, a batch processing environment. But then they'll take pieces of that data and want to do deep analytics on it, like a regression analytics, and they will put it into Vertica.

    Vertica is, is an analytic database platform, and I will break up those three words. It's a database. It looks and feels like a database. It has SQL on it, open database connectivity (ODBC), and Java database connectivity (JDBC) connectivity. You can run all kinds of tools on it, the ones you are used to, Tableau, Pentaho, and Informatica. So from that perspective it's a regular database.

    What's different is that it's custom built for the fourth wave. It's an analytic database, and by that, I mean the underlying algorithms are completely designed from the ground up. Michael Stonebraker who created the key products in the first wave and the second wave -- Ingres and Postgres -- also created this at MIT from the ground up.

    Data today

    The intuition was that if you look at the processing of data today, it's gone from having 10 to 20 columns per row to possibly thousands of columns. A social media company, for example, might have 10,000 pieces of information on me, and while they do processing, it's going more linear. It's going regression-oriented in a sense. You might say "Girish, age x, lives here, and likes y. What's the likelihood somebody else may like it?"

    It's meant for that kind of deep analytical processing, a column-oriented structure. In those kinds of applications, this database technology tends to be magnitudes faster -- tens of times faster. That's one example of Hadoop and Vertica, and we can talk more about other pieces Autonomy and Enterprise Security with you.

    Gardner: So we see that there's a platform that you put together. There's an ecosystem that's supporting that. There are these binding standards that make the ecosystem and the platform more synergistic. But other people are doing the same thing. What's making HAVEn different? What is it about HAVEn that you think is going to be a winner in the marketplace?

    Mundada: There are two different answers to it. Let me talk about how we've taken just not the SQL piece of Hadoop, but how we extend it with other parts of HP that are unique to HAVEn. It's the breadth of it. Let's see how we extend this simple combination of Hadoop and Vertica.

    I said it's an analytic database platform. If you look at that platform piece of it, with Vertica, we're able to drop in other code that are user-defined and user-written. For example, you can drop in R language routines, Java, C++, or C language routines directly into the database. Now, we're now able to combine that richness across our portfolio.

    Autonomy, which is the A part of HAVEn, is a unique technology. It's one of a kind. Some of the largest governments and some of the largest organizations in the world, such as banks and financial institutions, have this in production in what it's meant for, human information processing, which is audio, video, and text.

    As an example, you could take a video stream and ask simple questions. Tell me if an object is moving from point A to point B, or tell me what's in the object. Is it a human? Is it a car? Can you read car number plates automatically?

    And you could do some really sophisticated applications. Taking a car, we have cases where police cars have video cameras mounted on the side, and as they're driving by in a parking lot, they can take photos of the number plates and compare it to stolen cars.

    Crime detection

    Imagine being able to take that technology and combining it automatically, through simple SQL-like or simple REST API-like commands with SQL, with your existing data and creating very sophisticated applications to understand your customer or for crime detection and things like that?

    Now let's bring in the third of part of the puzzle, the E part, which is Enterprise Security. That's also unique. We have an entire portfolio, both for security as well as for operations management.

    If you look at enterprise security and if you look at the Gartner Magic Quadrant, HP's product set has been in the leader space for several years in a row. They are the number one vendor in that area.

    Now, think about our portfolio of ArcSight, Fortify, Tipping Point, and other ESP products. Imagine being able to take the data-collection algorithms of those, bringing it into this common platform of HAVEn, combining it with other structured and unstructured data with just simple commands. That's something we can do uniquely.

    Operations management is another area where we have hundreds of these machine logs. We can collect them, break them open into modular pieces, and create new applications. You can go look at our website, Operations Analytics, where with a simple slider, you can go back and forth in time to millions of log files as if they were structured data.

    We can do that uniquely, because we have that entire collection. Our BSM portfolio has been on the market for 30 years. It's one of the leaders. This is the HP OpenView platform and this is one of the things we can do uniquely at HP, bring all these things together.

    That's the breadth of our portfolio, but it simply doesn't stop at this platform level. Remember, I said that there are two concepts. There is a platform, and then there is the ecosystem. Let's look at the platform level first.

    We have the whole of HAVEn. We have the connectors, and we ship these 700 connectors out of the box. With simple commands, you can bring in social-media data in every language written. You can bring in machine logs and structured logs. That's the platform.

    Let's extend it further into the ecosystem part. The next thing that people were saying was, "We want to use something very open. We have our own visualization tools. We have our own extract, transform, load (ETL) tools that we're used to. Can you just make them work?" And we said, "Sure."

    That's one of the things that we're able to do now. With simple SQL, we can essentially write simple queries across structured and unstructured data. Using Tableau Software, or any other tool that you like, we can access this data through our connectors, but, more importantly, it let's you hook in your existing ETL tools into this -- completely transparently.

    Breadth and openness

    So that's the openness of the platform, the breadth and the openness of the platform. Breadth is not just about the software platform, but it's about HP's strength to bring together hardware, software, and services.

    Even with the platform, the HAVEn components in the middle, the connectors, and being able to match them with matching hardware, our customers are asking, "Can you give us matching hardware for Hadoop, so we don't have to spend time setting it up?" That's one of things that HP can uniquely do, but more importantly we have appliances for Vertica, for example, which are standardized.

    If you look at the other side, our customers are also saying, "We understand that HP wants to provide us all this, but we like openness and we like other partners." So we said, "Fine, we'll leave this entire ecosystem open." Our software will work with HP hardware and we can optimize, but we also commit to working on everybody else's hardware.

    Our cloud story is that we'll work on Amazon, as well as OpenStack. For example, if you want to build a hybrid cloud, where part of your data resides on HP or your private environment using OpenStack, that's fine. If you want to put it in Amazon or Rackspace, no problem. We'll help you bridge all these. These are the kinds of enterprise-cloud innovations that HP is able to do, and we're open to this.

    So to answer your question very succinctly, if there were three things I would pick where HP is different, one is our breadth of our portfolio. We have very large breadth that we've brought together.

    It's the openness of the platform. HP is known to be a very open company. If you look our Hadoop story, we have an example. We didn't create a proprietary Hadoop. We kept it open. If you look at our virtualization, we didn't go and force a virtualization technology on you. We kept it open.

    More importantly, if there is one key thing that you want to take home from what we've done with HAVEn, it's not about feeds and not about speeds. It's about business value.

    The reason we created HAVEn was to create that iPhone-like environment or Android-like environment, where the vision is that you should be able to go to a website, say you have standardized on the HAVEn platform, and then, be able to point and click and download an application.

    The end part of HAVEn is really the business value of it, and that's how we see HAVEn as unique. There is nobody else, as far as we know, that has that end-vision, where you can build the applications yourself using standard tools -- SQL, ODBC, REST API, JDBC -- or you can buy ready-made software that HP Software has created.

    We have packages across service, operations, and digital marketing. Or you can go with a partner. The partner could be HP Enterprise Services, Accenture, Capgemini, or any of those big partners. That's something unique about the HP big-data ecosystem that doesn't exist anywhere else today.

    Applications

    Gardner: Applications are something that take advantage of the platform, the capabilities, the breadth and depth of the data, and information.

    I wonder if you could explain a little bit more about the application side of HAVEn, perhaps through examples of what people are already doing with these applications, and how they're using them in their business setting?

    Mundada: That's actually one of the most exciting parts of my job. As I said, I meet literally 100 customers a month. I'm traveling across the continents, and the use-cases of big data that I see are truly phenomenal. It really keeps you very motivated to keep doing more.

    Let's look at a very broad level of why these things matter. Big data is not just about monetary profits. It's really about what I call extended profits. It doesn't have to be monetary. If you look at a simple example, we have medical companies using data, using our technologies, to dramatically speed up drug discovery hundreds of times more than they were able to with Hadoop.

    That translates into just saving lives. At our recent Discover show in Barcelona, we saw that a very innovative organization is using our technology to look at bio-diversity and save wildlife in the Amazon.

    That's unique, but those are like edge cases. If you look at a regular enterprise, what they want to do at a very high level falls into three categories: Applications that HP itself is building, applications that partners are building, and applications that customers themselves are building.

    There are three applications I'll mention. In terms of increasing revenue, we have a product that we ship called Digital Marketing Hub, and it combines the power of Autonomy and Vertica to analyze all of your customer analytics.

    You're able to take your call center logs, your social media feeds, your emails, your phone interactions and find out what the customer is really is saying, what they want and don't want, and then, being able to optimize that interaction with the customer to create more revenue.

    More precise answers

    For example, when a customer calls knowing what they want, obviously you can tell them more precise things. That's one example.

    Let's look at another example, where you want to decrease your bottom line or decrease your costs. Operational Analytics is another software product we ship. We're able to drive down costs of debugging network troubles by 80 percent by combining all these logs from machines on a very frequent basis.

    We can look at this and say. "At this second, every machine was okay. A second later, machines have gone down." I can look exactly at the incremental logs that showed up, using a simple pen like a pointer, going through SQL-like data. That's unique.

    Those are the kinds of applications we're able to create. It's not just these two. The other thing people want is improve products and services. We have something called Service Anywhere, where as you're calling or as you're typing in commands and saying you want to find information about that, the system is able to understand the meaning of what you're saying.

    Notice that this is not keyword search. This is meaning, where it's able to go through existing case reports from customers, look at existing resolutions, and then say, "Okay, this might solve your problem automatically."

    Imagine what that impacts. Your customers are happy, because the answers are quicker. We call this ticketless ID, but more important, look at some other interesting ways of how this affects a company.

    For example, I was recently in Europe. I was talking to a very large telco there, and they said, "We have something like 20,000 call-center operators who are taking calls from customers. Each call volume might take six minutes and some of them are repeat calls. That's really our problem."

    We worked out something that roughly could save them two minutes per call. That translates to about a $100 million net saving per year. That's really phenomenal. Those are one kind of application that HP built.

    Now imagine a customer wanting to build the same application themselves. That's the beauty of the HAVEn platform. On the same platform, you can buy HP built applications or you can build your own.

    Let's look at NASCAR as an example. They did something very similar for customer analytics. They are able to -- while the race is happening -- understand audio, television channels, radio, broadcast, and social media and bring that all together as if it's one unique piece of data.

    Then, they're able to use that data in really innovative ways to further their sport and to create more promotional dollars for just not themselves, but even the participants. That's unique -- being able to analyze mass scale human data.

    Looking to the future

    Gardner: Well, we've learned a lot about the market, the demand, why big data makes so much sense. There is very large undertaking by HP around HAVEn, and what it's getting in terms of openness, platforms, breadth, and these great examples of applications. But we also need to look to the future.

    What's coming next in terms of HAVEn 2.0 or HAVEn 1.5? Dan, could you update us on how things are progressing, what you have in mind for the next versions of these products and, therefore, the whole increasing as sum of the parts increases?

    Wood: Dana, we've just announced HAVEn 2.0. The way Girish explained HAVEn there in terms of the platform and the ecosystem and continuous innovation now is around both of those pieces. It's really important to us to be driving the ecosystem, as well as the platform. So I'll speak to HAVEn 2.0 and one of the feature that's the focus in driving HP forward.

    In terms of the platform, there are the analytics engines that we have. Girish mentioned they were best in class at the time that HP acquired them, and we continue to invest in R and D across Autonomy, IDOL, Vertica, and the ArcSight Logger product. We recently announced new versions of all three of those, improving the analytics capability and the usability and, just as importantly, increasing the interoperability.

    For example, we now have integration of the ArcSight Logger with the Autonomy IDOL engine for analyzing unstructured human information. A really great use case of this is Logger was previously enabling IT to understand data movements and potential threats and the risks in the organization.

    For example, if I were sending 50 percent of my email to a competitor, you could combine that capability with the unstructured information analysis in Autonomy and understand by that the information layer exactly what's in that email, 50 percent of which is going to a competitor.

    Let's start putting that together and getting a powerful view of what an individual is doing and whether it's a risky individual in the organization, integrating those HAVEn engines and putting more effort on integrating it into the Hadoop environment as well.

    For example, we have just announced integration Hadoop connectors for Autonomy. A lot of people are saying that they're building this data lake with Hadoop and they want to have the capability of putting some analytics into the unstructured information that exists in that Hadoop data lake. Clearly, we've also got integration with Vertica in the Hadoop environment as well.

    The other key thing within that on the engine is IDOL OnDemand. At the moment, on an early-access program, we're making the IDOL engine available to developers as a cloud-based offering. This is to encourage the independent developer community to take components of IDOL with that social media analytics, whether it's video or audio recognition, and start building that into their own applications.

    We believe the power of HAVEn will come from the combination of HP-provided applications and also third-party applications on top.

    Early-access program

    We're facilitating that with this initial early-access program on IDOL OnDemand, and also, we're investing in developer programs to make the whole HAVEn development platform far easier for partners and independent developers to work with.

    We've set up a HAVEn developer website, and stay tuned for some really fun events online and physical events, where we'll be getting the developer community together.

    In terms of those applications that make the whole HAVEn ecosystem come to life, Girish has mentioned some of them that we have announced over the last few weeks. So I'll give you a quick recap on those.

    We have the Operations Analytics and Service Anywhere apps, both aimed at the CIO. And we have the Digital Marketing Hub from HP aimed at marketing leaders in the organizations. These are three applications that HP has packaged on the HAVEn platform.

    And along with the HAVEn 2.0 announcement, we're really pleased that six of the leading SI partners -- Accenture, Capgemini, Deloitte, PwC, Accenture and Wipro -- themselves have put marketing applications on top of HAVEn. And those guys have gotten fascinating mixtures of very industry-specific analytics applications and more horizontal apps based on the priorities that they're chasing after.

    So we're really excited about that and expect to see many more announcements of partner applications over the next few months.

    The final piece of HAVEn 2.0 to support this whole ecosystem thing is a marketplace that we've launched, where we're populating our solutions and partner solutions to facilitate the whole commerce side of those applications taking off in the market.

    One-stop resource

    The first place to go is hp.com/haven. That's your one-stop resource for information on this platform, all of the engines that Girish alluded to. You can get the inspiration from some amazing customer case studies we have on there -- insights from experts like Girish and other people who are talking in depth about the individual engines.

    And as you rightly say, Dana, it's finding the right on-ramp for yourself. You can look at the case studies we have, the use cases on big data in particular industries, and take a look at what the specific pain point you have today. That's the hp.com/haven website, and that gives you all of that information.

    You can also drill down from there, if you're a developer, and find the tools and resources that we've spoken about to enable you to start building apps on top of HAVEn. That's one part.

    The whole power of HP behind this HAVEn platform is in enabling, from an infrastructure and services point of view, to start building these big data analytics. A couple of key things here.

    We started to build fully configured appliances around Hadoop and Vertica. So the Converged System's team in HP has launched the ConvergedSystem 300, which enables you to have Vertica and Hadoop on a pre-configured appliance. That's a great starting point for someone early on in the big-data analytics life cycle.

    To expand on that, the Technology Services team is able to do full consulting on how to optimize the overall infrastructure from the point of view of processing, sharing, and storing this vast amount of information that all organizations are coping with today. That will then start to put in things like 3PAR storage systems and other innovations across the HP hardware business.

    Another place where I see customers often needing some help to get started is in understanding exactly what the questions are that we need to be asking in terms of analytics and exactly what algorithms and analytics we need to put in place to get going. This is where the Big Data Discovery Experience Services from HP come in.

    This is provided by the Enterprise Services Group (ESG). Those guys have data scientists and industry experts who can actually help customers go through the design phase for a big-data platform and than offer the HAVEn infrastructure supported by the ESG Services team.

    Finally, Dana, come and see us on the road. We'll be at HP Discover in Las Vegas June 10-12. We're putting together several road shows and events across the main regions in Europe, the Americas, and in Asia Pacific, where we will be taking HAVEn on the road, too. Take a look at that hp.com/haven website, and details of the events will be found on there.

    Key messages

    Mundada: There are two key messages: big data is really important and it's disrupting business. Your competitors are going to do it. You have a choice to either lead and do it yourself or you will be forced to follow. It's one of those things that are disrupting industries worldwide.

    Now, when you think of big data, don't think of pieces and don't think of piece parts. It's not like you need a separate solution for human information, another for machine logs, and another for structured data. You almost have to think of it holistically, because there are many kinds of newer applications that I'm seeing regularly, where you have to bring all these data types together and create joint applications.

    Whichever technologies that you choose and settle on, think of that Microsoft Office-like experience. You want to combine integrated solution across the entire stack and there aren't that many available in the market today. So whoever you work with, make sure that you're able to handle that entire piece as one giant puzzle.

    Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

    You may also be interested in:
    Mar 10 6:04 PM | Link | Comment!
  • Fast-Changing Demands On Data Centers Drive Need For Uber Data Center Infrastructure Management

    Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

    Once the province of IT facilities planners, the management and automation of data centers has rapidly grown in scope and importance.

    As software-driven data centers have matured and advanced to support unpredictable workloads like hybrid cloud, big data, and mobile applications, the ability to manage and operate that infrastructure efficiently has grown increasingly difficult.

    At the same time, as enterprises seek to rationalize their applications and data, centralization and consolidation of data centers has made their management even more critical -- at ever larger scale and density.

    So how do enterprise IT operators and planners keep their data centers from spinning out of control despite these new requirements? How can they leverage the best of converged systems and gain increased automation, as well as rapid analysis for improving efficiency?

    BriefingsDirect recently posed such questions to two experts from HP Technology Services to explore how new integrated management capabilities are providing the means for better and automated data center infrastructure management (DCIM).

    To learn more on how disparate data center resources can be integrated into broader enterprise management capabilities and processes, now join Aaron Carman, HP Worldwide Critical Facilities Strategy Leader, and Steve Wibrew, HP Worldwide IT Management Consulting Strategy and Portfolio Lead. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions. [Learn more about DCIM.]

    Here are some excerpts:

    Gardner: What's forcing these changes in data center management and planning and operations? What are these big new requirements? Why is it becoming so difficult?

    Carman: In the past, folks were dealing with traditional types of services that were on a traditional type of IT infrastructure. Standard, monolithic-type data centers were designed one-off. In the past few years, with the emergence of cloud and hybrid service delivery, as well as some of the different solutions around convergence like converged infrastructures, the environment has become much more dynamic and complex.

    Hybrid services

    So, many organizations are trying to grapple with, and deal with, not only the traditional silos that are in place between facilities, IT, and the business, but also deal with how they are going to host and manage hybrid service delivery and what impact that's going to have on their environment.

    Carman

    It's not only about what the impact is going to be on rolling out new infrastructure solutions like converged infrastructures from multiple vendors, but how to increasingly provide more flexibility and services to their end users as digital services.

    It's become much more complex and it's a little bit harder to manage, because there are many, separate types of tools that they use to manage these environments, and it has continued to increase.

    Gardner: Steve, I suppose too that with ITIL v3 and more focus on a service-delivery model, even the very goal of IT has changed.

    Wibrew: That's very true. We're seeing a trend in the change and role of IT to the business. Previously IT was a cost center, an overhead to the business, to deliver the required services. Nowadays, IT is very much the business of an organization, and without IT, most organizations simply cease to function. So IT, its availability and performance, is a critical aspect of the success of the business.

    Gardner: What about this additional factor of big data and analysis as applied to IT and IT infrastructure? We're getting reams and reams of data that needs to be used and managed. Is that part of what you're dealing with as well?

    Wibrew

    Wibrew: That's certainly a very important part of the converged-management solution. There's been a tremendous explosion in the amount of data, the amount of management information, that's available. If you narrow that down to the management information associated with operating management and supporting data centers from the facility to the applications, to the platforms right up to the services to the business, clearly that's a huge amount of information that's collected or maintained on a 24×7 basis.

    Making good and intelligent decisions on that is quite a challenge for many organizations. Quite often, we would be saying that people still remain in isolated silo teams without good interaction between the different teams. It's a challenge trying to draw that information together so businesses can make intelligent choices based on analytics of that end-to-end information.

    Gardner: Aaron, I've heard that word "silo" now a few times, siloed teams, siloed infrastructure, and also siloed management of infrastructure. Are we now talking about perhaps a management of management capabilities? Is that part of your story here now?

    Added burden

    Carman: It is. For the most part, most organizations when faced with trying to manage these different areas, facilities IT and service delivery, have come up with their own set of run books, processes, tools, and methodologies for operating their data center.

    When you put that onto an organization, it's just an added burden for them to try to get vendors to work with one another and integrate software tools and solutions. What the folks that provide these solutions have started to realize is that there needs to be an interoperability between these tools. There has never really been a single tool that could do that, except for what has just emerged in the past few years, which is DCIM.

    HP really believes that DCIM is a foundational, operational tool that will, when properly integrated into an environment, become the backbone for operational data to traverse from many of the different tools that are used to operate the data center, from IT service management (ITSM), to IT infrastructure management, and the critical facilities management tools.

    Gardner: I suppose yet another trend that we're all grappling with these days is the notion of things moving to as-a-service, on-demand, or even as a cloud technology. Is that the case, too, with DCIM, that people are looking to do this as a service? Are we starting to do this across the hybrid model as well?

    Carman: Yes. These solution providers are looking toward how they can penetrate the market and provide services to all different sizes of organizations. Many of them are looking to a software-as-a-service (SaaS) model to provide DCIM. There has to be a very careful analysis of what type of a licensing model you're going to actually use within your environment to ensure that the type of functionality you're trying to achieve is interoperable with existing management tools. [Learn more about DCIM.]

    Wibrew: Today, clients have a huge amount of choice in terms of how they provision and obtain their IT. Obviously, there are the traditional legacy environments and the converged systems and clients operate in their own cloud solutions.

    Or maybe they're even going out to external cloud providers and some interesting dynamics that really do increase the complexity of where they get services from. This needs to be baked into that converged solution around the interoperability and interfacing between multiple systems. So IT is truly a business supporting the organization and providing end-to-end services.

    Organizations struggling

    Carman: Most organizations are really struggling to introduce DCIM into their environment, since at this point, it's really viewed as more as a facilities-type tool. The approach from different DCIM providers varies greatly on the functions and features they provide in their tool. Many organizations are struggling just to understand which DCIM product is best for them and how to incorporate into a long term strategy for operations management.

    So the services that we brought to market address that specifically, not only from which DCIM tool will be best for their environment, but how it fits strategically into the direction they want to take from hosting their digital services in the future.

    Gardner: Steve, I think we should also be careful not to limit the purview of DCIM. This is not just IT. This does include facilities, hybrid and service delivery model, management capabilities. Maybe you could help us put the proper box around DCIM. How far and why does it go or should we narrow it so that it doesn't become deluded or confused?

    Wibrew: Yeah, that's a very good question, an important one to address. What we've seen is what the analysts have predicted. Now is the time, and we're going to see huge growth in DCIM solutions over the next few years.

    DCIM has really been the domain of the facilities team, and there's traditionally been quite a lack of understanding of what DCIM is all about within the IT infrastructure management team. If you talk to lot of IT specialists, the awareness of DCIM is still quite limited at the moment. So they certainly need to find out more about it and understand the value that DCIM can bring to IT infrastructure management.

    I understand that features and functions do vary, and the extent of what DCIM delivers will vary from one product to another. It's very good certainly around the facilities space in terms of power, cooling, and knowing what's out on the data center floor. It's very good at knowing what's in the rack and how much power and space has been used within the rack.

    It's very good at cable management, the networks, and for storage and the power cabling. The trend is that DCIM will evolve and grow more into the IT management space as well. So it's becoming very aware of things like server infrastructure and even down to the virtual infrastructure, as well, getting into those domains.

    DCIM will typically have work protectabilities for change in activity management. But DCIM alone is not the end-to-end solution, and we realized the importance of the need to integrate it with the full ITSM solutions and platform management solutions. A major focus, over the past few months, is to make sure that the DCIM solutions do integrate very well with the wider IT service-management solutions to provide that integrated end-to-end holistic management solution across the entire data-center ecosystem.

    Great variation

    Carman: With DCIM being a newer solution within the industry, I want to be very careful about calling folks DCIM specialists. We feel that we have a very great knowledge of the solutions out there. They vary so greatly.

    It takes a collaborative team of folks within HP, as well as with the client, to truly understand what they're trying to achieve. You could even pull it down to what types of use cases they're trying to achieve for the organization, which tool works best and in interoperability and coordination with the other tools and processes they have.

    We have a methodology framework called the Converged Management Framework that focuses on four distinct areas for a optimized solution and strategy for starting with business goals and understanding what the true key performance indicators are and what dashboards are required.

    It looks at what the metrics are going to be for measuring success and couples that with understanding organizationally who is responsible for what types of services we provide as an ultimate service to our end user. Most of the time, we're focusing on the facilities in IT organization. [Learn more about DCIM.]

    Also, those need to be aligned to the process and workflows for provisioning services to the end users, supported directly by a system's reference architecture, which is primarily made up of operational management tools and software. All those need to be supported by one another and purposefully designed, so that you can meet and achieve the goals of the business.

    When you don't do that, the time it takes for you to deliver services to your end user lengthens and costs money. When you have separate tools that are not referencing single points of data, then you're spending a lot of time rationalizing and understanding if you have the accurate data in front of you. All this boils down to not only cost but having a resilient operations, knowing that when you're looking at a particular device or setup devices, you truly understand what it's providing end to end to your users.

    Wibrew: If you think about the possibilities in the management of facilities, the IT infrastructure, right up to services of a business, end-to-end, is very large and very, very complex. We have to break it down into small or more manageable chunks and focus on the key priorities.

    Most-important priorities

    So we look at the trans-organization, work with them to identify to them what their most important priorities are in terms of their converged-management solution and their journey.

    It's heavily structured around ITSM and ITIL processes, and we've identified some great candidates within ITIL for integration between facilities in IT. It's really a case of working out the prioritized journey for that particular client. Probably one of the most important integrations would be to have a single view of the truth of operational data. So it would be unified asset information.

    CMDBs within a configuration management system might be the very first and important integration between the two, because that's the foundation for other follow-on services until you know what you've got, it's very difficult to plan, what you need in the future in terms of infrastructure.

    Another important integration that is now possible with these converged solutions is the integration of power management in terms of energy consumption between the facilities and the IT infrastructure.

    If you think about managing the power consumption of things like efficiency of the data center with PoE, generally speaking, in the past, that would be the domain of the facilities team. The IT infrastructure would simply be hosted in the facility.

    The IT teams didn't really care about how much power was used. But these integrated solutions can be more granular, far more dynamic around energy consumption with much more information being collected, not just at a facility level but within the racks and in the power-distribution units (PDUs), and in the blade chassis, right down to individual service.

    We can now know what the energy consumption is. We can now incentivize the IT teams to take responsibility for energy management and energy consumption. This is a great way of actually reducing a client's carbon foot print and energy consumption within the data center through these integrated solutions.

    Gardner: Aaron, I suppose another important point to be clear on is that, like many services within HP Technology Services, this is not just designed for HP products. This is an ecumenical approach to whatever is installed in terms of product facility management capability. I wonder if you could explain a bit more HP's philosophy when it comes to supporting the entire portfolio. [Learn more about DCIM.]

    Carman: HP's professional services we're offering in this space are really agnostic to the final solution. We understand that a customer has been running their environment for years and has made investments into a lot of different operational tools over the years.

    That's a part of our analysis and methodology, to come in and understand the environment and what the client is trying to achieve. Then we put together a strategy, a roadmap of different products, that will help them achieve their goals that are interoperable.

    Next level

    We continue to transform them to the next level of abilities or capabilities that they are looking to achieve, especially around how they provision services and help them become, at the end, most likely a cloud-service provider to their end users, where heavy levels of automation are built in, so that they can get digital services to their end users in a much shorter period of time.

    Gardner: I realize this is fairly new. It was just on Jan. 23 that HP announced some new services that include converged-management consulting, and that management framework was updated with new technical requirements. You have four new services organized with the management workshop, roadmap, design implementations, and so forth. [Learn more about DCIM.]

    So this is fairly new, but Steve Wibrew, is there any instance where you've worked with some organization and that some of the really powerful benefits of doing this properly have shown through? Do you have any anecdotes you can recall of an organization that's done this and maybe some interesting ways that it's benefited them, maybe unintended consequences?

    Data-center transformation

    Wibrew: The starting point is to understand what's there in the first place. I've been engaged with many clients where if you ask them about inventory, what's in the data center, you get totally different answers from different groups of people within the organization. The IT team wants to put more stuff into the data center. The facilities team says, "No more space. We're full. We can't do that."

    I found that when you pull this data together from multiple sources and get a consistent feel of the truth, you can start to plan far more accurately and efficiently. Perhaps the lack of space in the data center is because there may be infrastructure that's sitting there, powered on, and not being utilized by anybody.

    It's a fact that we're redundant. I've had many situations where, in pulling together a consistent inventory, we can get rid of a lot of redundant equipment, allowing space for major initiatives and expansion projects. So there are some examples of the benefits of consolidated inventory and information.

    Gardner: As we look a few years out at big-data requirements, hybrid cloud requirements, infrastructure KPIs for service delivery, energy, and carbon pressures? What's the outlook in terms of doing this, and should we expect that there will be an ongoing demand, but also ongoing and improving return on investments you make, vis-à-vis these consulting services and DCIM?

    Carman: Based upon a lot of the challenges that we outlined earlier in the program, we feel that in order to operate efficiently, this type of a future state operational-tools architecture is going to have to be in place, and DCIM is the only tool poised to become that backbone between the facilities and IT infrastructures.

    So more-and-more, with a lot of the challenges of my compute footprint shrinking and having a different requirements that I had in the past, we're now dealing with a storage or data explosion, where my data center is all filled up with storage files.

    As these new demands from the business come down and force organizations onto new types of technology infrastructure platforms they haven't dealt within the past, it requires them to be much more flexible when they have, in most cases, very inflexible facilities. That's the strength of DCIM and what it can provide just in that one instance.

    But more-and-more, the business is expecting digital services to almost be instant. They want to capitalize on the market at that time. They don't want to wait weeks or months for enterprise IT to provide them with a service to take advantage of a new service offering. So it's forcing folks into operating differently, and that's where converged management is poised to help these customers.

    Looking to the future

    Gardner: Steve, when you look into your crystal ball and think about how things will be in three to five years, what is it about DCIM rather and some of these services that you think will be most impacting?

    Wibrew: I think the trend we're going to see is a far greater adoption of DCIM. It's only deployed in a small number of data centers at the moment. That's going to increase quite dramatically, and this could be a much tighter alignment between how the facilities are run and how the IT infrastructure is operated and supported. It could be far more integrated than it is today.

    The roles of IT are going to change, and a lot of the work now is still around design, planning, scripting, and orchestrating. In the future, we're going to see people, almost like a conductor in an orchestra, overseeing the operations within the data center through leading highly automated and optimized processes, which are actually delivered by automated solutions.

    Gardner: I benefited greatly in learning more about DCIM on the HP website. There were videos, white-papers, and blog-posts. So, there's quite a bit of information for those interested in learning more about DCIM. HP Technology Services website was a great resource for me. [Learn more about DCIM.]

    Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

    You may also be interested in:
    Mar 07 2:10 PM | Link | Comment!
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