How Small & Medium Sized Businesses Can Tap Into Big Data and Analytics

By Rahul Agarwal, 

Importance of business analytics

The importance of analytics in today’s business environment cannot be overemphasized. You need clear and rapid insights into your business in order to drive profits, optimally allocate increasingly scarce resources, exploit new opportunities, and proactively respond to risks.  Without such insights, you may take a longer time to arrive at decisions or you may make incorrect decisions that are influenced by limited data or intuition.

A study by Bain & Company has found that companies with the best analytic capabilities outperform the competition in financial performance and in making effective business decisions[1].

Another study by IBM Institute for Business Value recognizes speed of acquiring, analyzing and acting on business data as a source of competitive advantage.[2]

Why do small and medium businesses need analytics

The need for analytics is even more pronounced for a small business. Your bigger competitors could already be using insights from their enterprise data to increase the efficiency of their business operations across product development, marketing and customer service. This can pose a threat to your business and you need insight into your business operations in order to take the right decisions to stay a step ahead of your competition.  In addition, given that you have limited resources, you should be able to monitor and validate if your investments are delivering an expected increase in sales and profits on an ongoing basis. Without these insights, you risk your business being made irrelevant, as it will be extremely hard to ensure profitable and sustained growth of your enterprise.

What should a small/medium sized look for from their analytic solution

Initiating an analytics program can be intimidating especially given the perception that it requires a lot of IT expertise and is timely and costly to implement. So,  if you do not have the budget to invest in larger systems and perhaps cannot afford to hire database administrators and data scientists to operate new systems, you should look for a solution with the following characteristics:


The analytic system should be simple to manage and maintain, requiring minimal up front design and tuning to load data and execute queries. It should provide easy connectivity to leading extract, transform, and load (ETL), business intelligence, and analytic applications through standard interfaces.


It should be smart enough to allow quantitative teams to operate on the data directly inside the analytic system instead of having to offload it to a separate infrastructure and deal with the associated data pre-processing, transformation and movement.


It should be easily incorporated into your data center with simplified installation. Ideally, integration of hardware, software, and storage should be done for you, as this will lead to shorter deployment cycles and excellent time to value for your business intelligence and analytic initiatives.


The price should be set right, according to the size and capacity of the system.

At the same time, the analytic system should not compromise on speed, security, reliability and high availability.

PureData System for Analytics  N3001-001

The new PureData System for Analytics  N3001-001 is an appliance that possesses these characteristics. It is designed to deliver fast performance for complex analytics in a powerful and cost-effective solution allowing your business to transition from intuition-driven to an analytics-driven one.  As my colleague, Isaac Moreno Navarro puts it in his blog “If you have a small or midsize business, this is a great opportunity for you to enter the world of big data”.

You can learn more by looking at the data sheet for PureData System for Analytics  N3001-001  here.

About Rahul Agarwal

Rahul Agarwal is a member of the worldwide product marketing team at IBM that focuses on data warehouse and database technology. Rahul has held a variety of business management, product marketing, and other roles in other companies including HCL Technologies and HP before joining IBM.  Rahul studied at the Indian Institute of Management, Kozhikode and holds a bachelor of engineering (electronics) degree from the University of Pune, India. Rahul’s Twitter handle :  @rahulag80




The Combined Value of IBM Cognos and PureData System for Analytics

By Rich Hughes,

“A picture is worth a thousand words” is an adage that has weathered the test of time.  Other than noting this blog runs only about 600 words, the old saying captures the essence of modern visualization where complex data sources and entity interactions can be meaningfully refined into a single picture.  And now there are better ways to convert your data analysis into the most effective visual representation.  IBM Cognos® is quite helpful in this regard, providing the RAVE system, a platform which enables business users to develop appealing data graphics.

IBM’s Rapidly Adaptive Visualization Engine (RAVE) requests input and interaction from the user on how the graphical picture should look.  Based on IBM patented technology and concepts outlined in Wilkinson’s The Grammar of Graphics, RAVE produces the best visualization for the described circumstances. One could think of RAVE as a user productivity tool, and as an extension of the IBM Cognos Business Intelligence (BI) basic charter: insulating the business user from the nitty gritty of both SQL optimization and maximizing performance from relational databases.

For data to be useful, business users must feel comfortable working with integrated business data like finance, sales, product, and marketing entities.  Becoming routine is the further interweaving of social media, demographic, and competitor information to gain a complete view of one’s customer base.  The IBM® PureData™ System for Analytics is the appliance standard for simply delivering this type of integrated data warehouse.

IBM Cognos®, combined with PureData System for Analytics, provides leading business intelligence and enterprise scalability for reporting, interactive analysis, scorecards, and dashboards. As hinted earlier, IBM Cognos® out-of-the-box, supplies 25 data visualization graphics like Treemap, Waterfall, and Bubble charts.  IBM Cognos® will push these stunning business intelligence images out to mobile devices. IBM Cognos BI exploits Netezza analytic in-database functions, and improves upon the PureData System for Analytics by adding in-memory and caching techniques on top of fast appliance performance.

Blue Cross Blue Shield of Massachusetts (BCBSMA) is a great example of leveraging both Cognos and PureData System for Analytics.  Serving nearly 3,000,000 members from its Boston headquarters, BCBSMA uses this technology to imbed analytics into their day-to-day processes for a wide range of decision makers.  PureData System for Analytics fits the bill for a fast performing, centralized data warehouse by creating health informatics cubes in around six hours, an improvement of about 500%. This speed advantage enabled Cognos BI queries to deliver cubes with more dimensions, which thereby answered more business questions.

Blue Cross Blue Shield of Massachusetts medical directors are now able to ascertain different disease category levels at participating hospitals.  Using current and historical data, trends are spotted—providing the opportunity to actively intervene.  Benefits and care management can be designed based on this data analysis:  members with high cholesterol needed, and got help with specific programs aimed at reducing their risk of developing more serious heart problems.  Data driven decisions, a more informed and involved business community, and better health outcomes for its members are significant results from BCBSMA utilizing IBM Cognos® and PureData System for Analytics.

More information on the IBM® PureData™ System for Analytics N3001 family can be viewed at this LINK.    Included with the IBM PureData System for Analytics N3001, which was announced for General Availability on October 17, 2014, are IBM Cognos® Business Intelligence 10.2.1 software entitlements for five analytics user licenses and one analytics administrator license; these licenses can then be used when the IBM® PureData System for Analytics N3001 is your analytics data source. Particulars on Cognos combined with PureData System for Analytics will be found HERE, while Cognos BI details can be located at this URL.  A fuller treatment of the BCBSMA technology can be found on this link: BlueCross BlueShield of Massachusetts . The IBM® PureData™ System for Analytics N3001 is again changing the game for data warehouse appliances.

Figure 1: A Waterfall chart shows cumulative effects of values over time.
Figure 1: A Waterfall chart shows cumulative effects of values over time.
Figure 2: Treemaps reveal exceptions and patterns using size and color.
Figure 2: Treemaps reveal exceptions and patterns using size and color.

About Rich Hughes,

Rich Hughes is an IBM Marketing Program Manager for Data Warehousing.  Hughes has worked in a variety of Information Technology, Data Warehousing, and Big Data jobs, and has been with IBM since 2004.  Hughes earned a Bachelor’s degree from Kansas University, and a Master’s degree in Computer Science from Kansas State University.  Writing about the original Dream Team, Hughes authored a book on the 1936 US Olympic basketball team, a squad composed of oil refinery laborers and film industry stage hands. You can follow him on @rhughes134

The Logical Data Warehouse : Two Easy Pieces (DW+Hadoop)

By Dennis Duckworth,

In some of our recent blogs, we have described our Data Warehouse Point of View and our Zone Architecture for Big Data. We developed these from our experiences with our customers, seeing what worked (and what didn’t), to encourage those who are just starting out on their analytics journeys or those who are disappointed by the performance or rigidity of their existing data warehouse environments to at least consider the advantages of separating data (and corresponding analytics) into different zones based on the characteristics of both. We have been using the term Data Warehouse Modernization to describe the renovation of old traditional monolithic data warehouses (along with other data silos) into hybrid, integrated, or logical data warehouse models.

In a sort of modernization of our own, we have reexamined how we go to market with our data warehouse and data management products to see how we might make it easier for our customers to implement the best practices that we actively promote. With the recent release of our latest data warehouse appliance, the PureData System for Analytics (PDA) N3001 (codename Mako), we had the chance to make some changes. Now,  for example, included with every PDA appliance we ship (every configuration, from the smallest, the “Mako-mini” 2 server rack-mountable appliance, all the way up to our largest, our 8-rack system), we include license entitlements for other IBM software products we firmly believe can help our customers in creating a modern, flexible, high performance logical data warehouse environment. One of those entitlements is for IBM InfoSphere BigInsights for Hadoop.

Studies are proving out our opinion that the logical data warehouse is a critical contributor to analytic success for enterprises. In the recently released 2014 IBM Institute for Business Value analytics study, companies were analyzed and categorized by the extent and the effectiveness of analytics in them. Those in the top category, the “front runners”, use data to the highest benefit. They have been successful in “blending” their traditional business intelligence infrastructures with big data technologies to create agility and flexibility in the way they ingest, manage and use data. Quite interestingly, and consistent with our guidance in these blogs, almost all of the front runners (92 percent) have an integrated (or hybrid) data warehouse and, as part of that, they are 10 times than more likely than other organizations to have a big data landing platform. In practice, they have implemented what we have called zone architecture to allow them to collect and analyze a wider variety of data, empowering their employees to make full use of their traditional data and new types of data together.

DL 1

Our customers are also providing proof that data warehouse modernization works. How are these customers using BigInsights and these big data landing platforms? Many are creating what we have been calling data reservoirs. As you may recall from our blogs here and from the hundreds/thousands of other posts on the topic, Hadoop is finding a home in the enterprise as the preferred technology for data reservoirs. These are landing areas for all the data you think may be useful in your company, whether it is structured, unstructured, or semi-structured. Some more specific examples: One of our customers is using BigInsights in combination with the PureData System for Analytics to help it convert users of its free cloud service to customers for their paid service, using predictive analytics on user behavior (structured and unstructured data) to target them more accurately with offers. Another, a telco, is using BigInsights with PDA along with InfoSphere Streams to get a 360° view of its customers and to enable them to react in real-time to customer satisfaction issues. (The InfoSphere Streams entitlement with PDA will be the topic of a future blog.)

The BigInsights entitlement that comes with the N3001 PureData System for Analytics is for 5 virtual nodes which, by our calculations, gives you the ability to manage about 100TB of data. So this is not a useless little demo version – this license gives you the ability to create and use a full-blown Hadoop cluster with all of the advantages that BigInsights has to offer, things like Big SQL for SQL access to the data in BigInsights, Big Sheets (enables Excel like spreadsheet exploration of the data), text analytics accelerator, Big R (which allows you to explore, visualize, transform, and model big data using familiar R syntax), and a long list of other features and capabilities. You get all of this (and much more) with every N3001 PureData System for Analytics. With software entitlements like this, we allow you to practice what we preach: modernize your data management environment by putting data and the corresponding analytics on the proper platform.

About Dennis Duckworth

Dennis Duckworth, Program Director of Product Marketing for Data Management & Data Warehousing has been in the data game for quite a while, doing everything from Lisp programming in artificial intelligence to managing a sales territory for a database company. He has a passion for helping companies and people get real value out of cool technology. Dennis came to IBM through its acquisition of Netezza, where he was Director of Competitive and Market Intelligence. He holds a degree in Electrical Engineering from Stanford University but has spent most of his life on the East Coast. When not working, Dennis enjoys sailing off his backyard on Buzzards Bay and he is relentless in his pursuit of wine enlightenment. You can follow Dennis on Twiiter 

Data Warehousing – No assembly required

By Wendy Lucas,

In my last blog, I wrote about how big things come in small packages when talking about the great value that comes in the new PureData System for Analytics Mini Appliance.  I must be in the holiday spirit early because I’m going to stick with the holiday theme for this discussion.

Did youWL 1 ever receive a gift that had multiple components to it, maybe one that required a bunch of assembly before you got to truly enjoy the gift?   I’m not talking about Lincoln Logs (do they still sell those?) or Legos where the assembly is half the fun.

I’m talking about things like a child’s bicycle that comes with the frame, handle bar, wheels, tires, kickstand, seat, nuts and bolts as a bunch of parts inside a box.

What is more exciting? Receiving a box of parts or receiving the shiny red bicycle already assembled and ready to take for an immediate ride?

WL 2

In this world where we require instant satisfaction and immediate results, we don’t have time to assemble the bike. Do your system administrators have time to custom build a solution of hardware and software for your data warehouse?  Forget about that hardware and software being truly designed, integrated and optimized for analytic workloads.  What value are your users getting while the IT staff are doing that?  Do your DBAs have enough time to tune the system for every new data source that’s added or every new report requirement that one of your users needs?  We live in a world that demands agile response to changing requirements and immediate results.

Simple is still better for faster deployment

In this very complex world, simple solutions are better.  Just like the child preferring the bike that is already assembled and ready to go, the IBM PureData System for Analytics, powered by Netezza technology has been delivering on the promise of simplicity and speed for over a decade.  Don’t just take my word for it.  In a recent study, International Technology Group compared costs and time to value with PureData compared to both Teradata and Oracle.[i]   They researched customers deploying all three solutions and had some notable findings.  While over 75% of PureData customers deployed their appliances in under 3 weeks, not a single Teradata customer deployed in that same time frame and only one Oracle customer achieved that window.

Simple is still better for lower costs

Not only is the data warehouse appliance simple to deploy but it is architected for speed with minimal tuning or administration.  The same studies found that Teradata has 3.8x and Oracle 3.5x higher deployment costs than PureData System for Analytics and use more DBA resources to maintain the system.

Simple is still better, and now even more secure

The PureData System for Analytics N3001 series that was just announced has the same speed and simplicity of it’s predecessors, but adds improved performance, self-encrypting drives and big data and business intelligence starter kits.  The self-encrypting drives encrypt all user and temp data for added security without any performance overhead or incremental cost to the appliance.

For more anecdotal examples of why simple is still better, watch this video or you can read this white paper or visit for more information.

[i] ITG: Comparing Costs and Time to Value with Teradata Data Warehouse Appliance, May 2014.

ITG: Comparing Costs and Time to Value with Oracle Exadata Database Machine X3, June 2014.

About Wendy,

Wendy Lucas is a Program Director for IBM Data Warehouse Marketing. Wendy has over 20 years of experience in data warehousing and business intelligence solutions, including 12 years at IBM. She has helped clients in a variety of roles, including application development, management consulting, project management, technical sales management and marketing. Wendy holds a Bachelor of Science in Computer Science from Capital University and you can follow her on Twitter at @wlucas001