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Data-Driven Decision Making with the Vertica Analytics Platform

Physicians need access to a wealth of critical information from multiple systems in order to make life-saving decisions on a daily basis. Greg Gootee, Product Manager, MZI Healthcare, discusses how their new application, powered by the Vertica analytics platform, helps deliver better patient care through data-driven decision making. Delivering information in a timely manner is central to their application’s success. Check out this video shot at HP Discover 2013 to see how HP Vertica helps Greg and his team provide physicians with the information they need to make more accurate point-of-care decisions. In the video Mr. Gootee recounts how his Aunt may have avoided a tragic incident with better point-of-care services–the type of services MZI Healthcare and the Vertica analytics platform provide.

A Sneak Peek of HP Vertica Pulse, Harnessing the Volume and Velocity of Social Media Data

The Web provides us with a myriad of ways to express opinion and interest—from social sites such as Twitter and Facebook to blogs and community forums to product reviews in ecommerce sites to many more. As a result, customers have significant influence in shaping the perceptions of brands and products. The challenge for the managers of those entities on which opinion and interest is expressed is to understand, in an automated way and in as close to real-time as possible, what people are talking about and how they feel about those topics, so that they can better understand and respond to their community.

HP Vertica Pulse — now in private beta — is HP’s scalable, in-database answer to the problem of harnessing the volume and velocity of social media data. Executed through a single line of SQL, HP Vertica Pulse enables you to extract “attributes,” or the aspects of a brand, product, service, or event that your users and customers are talking about; and the ability to assign a sentiment score for each of these attributes, so that you can track your community’s perception on the aspects of your business that your community cares about. Understand whether your customers are looking for a particular feature, how they react to a facet of your product or service as you anticipated, or if they are suddenly encountering problems. See how their perceptions change over time.

We used HP Vertica Pulse at HP Discover to capture attendee sentiment. We captured tweets related to HP Discover, the Tweeter’s screen name, and the timestamp. We ran the tweets through HP Vertica Pulse and visualized the results in Tableau. The whole effort was up and running in just a few hours. The screenshot below shows the major aspects:



 

  • We watched the interest of the crowd change over time. With each successive keynote, we saw new initiatives and people appear in the word cloud. Meg Whitman received a lot of press, as did HP’s New Style of IT and HAVEn. So did Kevin Bacon, who participated in Meg’s keynote.
  • HP Vertica Pulse surfaced news in the data analytics world. In a trial run using tweets related to data analytics, we saw “Walmart” — not a common name in the world of analytics — appear in the word cloud. A quick drilldown in Tableau revealed that Walmart recently purchased data analytics company Inkiru.
  • We captured the most prolific Tweeters. We could expand on this data to include influencer scores and reach out to the most influential posters.
  • We captured sentiment on all of the tweets. In a friendly forum like HP Discover, we expect the majority of the tweets to be neutral or positive in nature.

HP Vertica Pulse is a result of an ongoing collaboration with HP Labs and is built on Labs’s Live Customer Intelligence (LCI) technology. The Labs team has already had great success with LCI as evidenced in part by their Awards Meter application. HP Vertica has also built a social media connector that loads tweets of interest directly from Twitter into the HP Vertica Analytics Platform, allowing you to start understanding your community right away.

HP Vertica Pulse is yet another example of how you can use the HP Vertica Analytics Platform to bring analytics to the data, speeding analysis time and saving the effort of transferring your data to an external system. Because HP Vertica Pulse is in-database, you can store your text data and the associated sentiment alongside sales, demographic, and other business data. HP Vertica Pulse will help you to harness the voice of your customer so that you can better serve them.

We are now accepting applications to trial Pulse in our private beta. To participate, contact me, Geeta Aggarwal, at gaggarwal@vertica.com.

Join us on Monday for an Open House

We’ve been sprucing up our gorgeous office space with help from our friends at Engage Marketing Design and are looking forward to showing it off on Monday.

Please join us by clicking this link and RSVP’ing. All friends of HP Vertica are welcome though space is limited and filling fast!

It’s coming together nicely – see below for a few previews – we’ll be taking more photos on Monday and want you in them. Join us and learn more about Boston’s Biggest Data!

Taking a Moonshot at Big Data Analytics for Everyone

HP Vertica is very excited about Monday’s announcement of the HP Moonshot system.

Why? Because we believe that the combination of the HP Vertica Analytics Platform running on the HP Moonshot Servers offers a truly game-changing value proposition for a variety of customers, and new segments of the market.

Moonshot is, simply put, a groundbreaking system which offers customers the ability to rapidly deploy, scale and manage with dramatically lower space and energy constraints. While traditional IT services that support business functions will continue to be served by general purpose server infrastructure, a new computing platform is required for specialized workloads that can deliver innovative solutions to market at unprecedented speed and scale.

 

We’ve already successfully tested the HP Vertica Analytics Platform on HP Moonshot Servers, and achieved very comparable performance to traditional Big Data Analytics hardware across certain performance ranges, which for a large segment of the market is more than sufficient to handle their Big Data Analytics loads – while offering very significant potential cost, space and energy savings.

Running Vertica on Moonshot offers yet another proof point of the unmatched value provided by HP’s combination of Information Optimization solutions, and a great example of the opportunity created by innovation that makes us so excited to be a part of the greater OneHP.

To learn more about HP Project Moonshot, visit http://www.hp.com/go/moonshot

Join HP Vertica’s User-Driven Community!

We at HP Vertica are very excited to announce our new user-driven community that will help us better serve our users, partners, and anyone generally interested in learning more about the HP Vertica Analytics Platform. In partnership with GetSatisfaction, community members can now:

  • Start engaging with other customers to establish new and valuable relationships
  • Add context to your past issues and get the best possible answers to your questions
  • Wield your influence as subject matter expert in the community

Now, HP Vertica newbies as well as seasoned database/data analytics veterans and everyone in between can post questions, share ideas, report issues, and give praise. To make this information readily available for your convenient access, all questions are cataloged and searchable.

The new-and-improved community interface will enable you to easily access more information and better communicate with HP Vertica and other users of the HP Vertica Analytics Platform.

We welcome you to join our community by visiting http://community.vertica.com or by accessing the community tab on the side of the www.vertica.com homepage.

Big Data Analytics without Big Data Complexity

New analytics deployments can be complex, taking up to 18 months to implement and optimize. The complexity of maintaining and integrating these environments often results in missed deadlines, incomplete projects, increased costs, and lost opportunities. In fact, only 32 percent* of application deployments are rated as “’successful”’ by organizations.

To remove this Big Data complexity, we are pleased to announce the general availability of the HP AppSystem for Vertica. Following through on the initial announcement at HP Discover as part of the HP AppSystems portfolio, the HP AppSystem for Vertica ensures system performance and reduces implementation time from months to a matter of hours.

But what is an AppSystem and is it right for you?

Built on the HP Converged Infrastructure, the new HP AppSystem for Vertica is a fully pre-integrated technology stack that includes a specifically optimized hardware configuration, factory pre-loaded OS, and the HP Vertica Analytics Platform environment.

HP AppSystem for Vertica is ideal for organizations interested in accelerating time-to-business value with high-performance, massively scalable analytics at each layer of IT infrastructure — server, storage, network, and management. As a result, you can scale seamlessly, while adding capacity as your analytics needs for Big Data evolve.
We encourage you to learn more about the HP AppSystem for Vertica — and get started removing complexity to capitalize on your big data analytics initiatives.

* = CHAOS Summary 2009, Jim Johnson, Standish Group, April 2009

The Disruptive Power of Big Data

Aside from the sheer quantity of digital data created every day—about 2.5 exabytes1 —there’s more to Big Data than volume. Big Data offers enterprise leaders the opportunity to dramatically change the way their organizations operate to gain competitive advantage and find new revenue opportunities. But realizing the value Big Data promises requires a new approach. Traditional data warehouses and business intelligence tools weren’t built for the scale of Big Data, and can’t provide insight quickly enough to be useful or even keep up.

But this isn’t just a case of data growth outstripping technology growth. Big Data embodies fundamental differences that necessitate new approaches and new technologies. Big Data takes many forms, three in particular we’ll discuss here:

  • Transactional data
  • Sentiment and perceptual data based on conversations taking place in social media
  • Data from networked sensors—the so-called “Internet of Things”

Transactional Data

As businesses have expanded—and expanded onto the Internet—the volume of business transactions has grown. The Economist reported in 2010 that Wal-Mart processes more than 1 million customer transactions every hour and maintains databases exceeding 2.5 petabytes (million gigabytes)2. Imagine how those numbers have grown since then.

What’s even more critical is that companies can now capture not just sales transactions, but the detailed histories and clickstreams that lead to the sale. From web-based clickstream analysis to call data records, pre- and post-transaction histories are more robust than ever—and our ability to collect, analyze and act on that data must adjust accordingly.

The social media explosion

Today’s online customer has progressed well beyond accessing information. Today’s consumers are not only interacting and collaborating with each other, but they’re talking about and interacting with your brand. Facebook has more than 1 billion active subscribers3, and it’s estimated they share almost 700,000 individual pieces on content every minute. On Twitter, more than a billion tweets go out every two to three days4. (You can watch them mapped geographically in real-time at tweetping.net.)

Product reviews, user communities, forums and blogs allow consumers to generate content that contains critical insight for the business. The proliferation of user-generated content in these social channels has lead to new techniques and tools for “sentiment analysis”—the ability to measure emotion to determine how your company and brand are perceived.

The Internet of Things

The amount of information generated by devices rather than people is also growing explosively.
Mobile devices—and the apps people use on them—regularly broadcast individuals’ location, performance and other factors to the network. Retailers and distributors are using radio frequency identification (RFID), bar and QR codes to track inventory and enhance their supply chain and inventory performance. The healthcare industry seeks to improve care and reduce costs through remote patient monitoring. The automotive industry is embedding sensors in vehicles. And utilities are beginning to rely on smart meters to track usage. McKinsey Global Institute reports that more than 30 million networked sensors are in use in the transportation, automotive, industrial, utilities and retail sectors—and the number is growing by 30 percent every year.5

We recently presented a webinar on the Internet of Things and the Power of Sensor Data, which delves into this exciting area in much more detail.

Disrupting conventional analytics – developing a ‘conversational relationship with data’

Using Big Data to make operations more efficient, improve competitiveness and increase revenue is not about generating traditional statistics or producing standard reports.

Just as important as systems to collect and store data are systems to analyze and extract insight from that data. Without insight, you can’t gain new knowledge into your markets, your products and your operations.

When you have this insight at your disposal, you can act faster and with greater probability of success.

Extracting business value from Big Data requires a new approach. We believe that Big Data analytics is an iterative process. We describe it as developing a conversational relationship with your data. Analytics becomes a continuous improvement loop, which uses the results of analyses to frame better, more meaningful analyses, which, in turn, produce more definitive results. When results are available in minutes, analysts can ask, “What if?”

When properly applied, Big Data analytics enables business leaders to:

  • Understand market reaction and brand perception
  • Identify key buying factors
  • Segment populations to customize actions
  • Enable experimentation
  • Accurately predict outcomes
  • Reinvent and enhance inventory and supply chain systems and processes
  • Disrupt their industries, gain an edge over competitors and enable new business models

Big Data already proved its game-changing power during the 2012 U.S. presidential election. Obama campaign chairman Jim Messina said: “We were going to demand data on everything, we were going to measure everything…We were going to put an analytics team inside of us to study us the entire time to make sure we were being smart about things.”
And, in fact, Big Data analytics helped the Obama campaign ratchet up the three key levers in any election: voter registration, persuasion and turnout. Rolling Stone magazine singled out Messina and the campaign’s CTO, Harper Reed, as two among a handful of unsung heroes in Obama’s victory.

You can hear more about how HP Vertica contributed to the high-tech strategy behind Obama’s reelection in a recent webinar featuring Chris Wegrzyn, director of data architecture for the Democratic National Committee.

The traditional data warehouse won’t get it done

The concept of the data warehouse evolved in the 1980s. Then, data warehouses were simply databases into which data from multiple sources was consolidated for the purpose of query and reporting. But today, these systems fall short when confronted with the volume, velocity and variety of Big Data. Why? They fail to enable the conversational approach to data required by Big Data analytics.

Traditional databases and data warehouses don’t easily scale to the hundreds of terabytes or even petabytes needed for many Big Data applications. Data is often not compressed, so huge amounts of storage and I/O bandwidth are needed to load, store and retrieve data. Data is still stored in tables by row, so access to a single data element through many rows—a common operation in business analytics—requires retrieving practically all of the data in a dataset to extract the specific element(s) needed. That strains I/O bandwidth and extends processing time. We have seen cases where the velocity of incoming data exceeds the capacity of the system to load it into the database, and queries produce answers in hours rather than the seconds or minutes needed for iterative business analytics. As a result, systems cost too much to maintain, and they fail to deliver the insight business leaders seek.

Take sentiment analysis, for example. The goal is to extract meaningful information from unstructured data so results can be stored in databases and analyzed. But the formats of resulting data are less predictable, more varied and subject to change during iterative analytics. This requires frequent changes to relational database structure and to processes that load data into them. For IT, it means the iterative approach to extracting business insight from Big Data requires new approaches, new tools and new skills.

Challenges for business leaders

Big Data is not just a technical challenge. Gaining and applying business insight compels business leaders to adopt new and disruptive ways of thinking and working.
Successful leaders we have known in data-driven organizations become more familiar with the sources of data available to them. Rather than asking IT what information is available in the database, they view information as a key competitive asset and explore how insights might be extracted from it to offer immediate and sustainable competitive advantage.

A solution for Big Data analytics

HP Vertica Analytics Platform is a new kind of database designed from the ground up for business analytics at the scale of Big Data. Compared to traditional databases and data warehouses, it drives down the cost of capturing, storing and analyzing data. And it produces answers 50 to 1,000 times faster to enable the iterative, conversational analytics approach needed.

  • HP Vertica Analytics Platform compresses data to reduce storage costs and speed access by up to 90 percent.
  • It stores data by columns rather than rows and caches data in memory to make analytic queries 50 to 1,000 times faster.
  • It uses massively parallel processing (MPP) to spread huge data volumes over any hardware, including low-cost commodity servers.
  • It uses data replication, failover and recovery to achieve automatic high availability.
  • It includes a pre-packaged, in-database analytics library to handle complex analytics and development framework.
  • It supports the R statistical programming language so analysts can create user-defined analytics inside the database.
  • It dynamically integrates with Hadoop to analyze large sets of structured, semi-structured and unstructured data.

HP Vertica Analytics Platform means better, faster business insight at less cost.


Test drive the HP Vertica Analytics Platform at www.vertica.com/evaluate.


[1] “Big Data: The Management Revolution,” Andrew McAfee and Erik Brynjolfsson, Harvard Business Review, October, 1012.

[2]“Data, data everywhere,” The Economist, Feb 25, 2010.

[3]Facebook key facts.

[4] http://www.mediabistro.com/alltwitter/tweetping_b35247

[5] “Big data: The next frontier for innovation, competition, and productivity,” The McKinsey Global Institute, June 2011.

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