Creating an analytics superteam: 4 critical success factors for your analytics solution

Content Marketing Manager, IBM Analytics Platform, IBM

Coming to a theater near you—this summer, next summer and every year for the foreseeable future—superheroes are teaming up to save the world (even the galaxy) from calamity. It’s not surprising that superhero movies continue to draw a wide range of fans. There’s something unique about a team of individuals, powerful in their own right, who join forces to make the extraordinary possible.

Yet after the joys of a moviegoing Friday night have faded, returning to work on Monday can bring a sharp contrast. As I sit down to make informed decisions in my role as a marketer, far from witnessing a superteam working in synchronization, I often have difficulty doing something as simple as getting my computer to talk to my printer.

Perhaps you are experiencing something similar, particularly when it comes to analytics solutions. For example, even though you have done your due diligence in selecting analytics solutions to meet a widening array of needs, piece-part solutions that don’t play well together might be starting to take their toll on you—and the threat of data that can’t provide relevant insight constantly looms. What you need is an analytics superteam. But what would such a team look like?

Creating an analytics superteam

To provide suitable analytics solutions, such a superteam would need to incorporate four critical success factors: broad and deep analytics, agile data integration and governance, fluid and hybrid architecture, and an open and unified approach. Together, these would allow a team to comprehensively address analytics needs and to synergistically provide a better solution than its members could have individually produced. So let’s take a look at each member of this superteam.

Broad and deep analytics










Breadth and depth of analytics helps you derive insights from all types of data—not only using predictive and prescriptive analytics capabilities, but also using the streaming analytics capabilities needed for real-time insight. And different analytics users must be taken into account—for example, everyday business users might need a solution that guides them through their use of analytics, using smart and intuitive user interaction to derive insight.

Agile data integration and governance

But those analytics capabilities reach a new peak when paired with agile data integration and governance to enhance the quality of data that goes into analytics. Across data’s entire lifetime, integration and governance abilities aid discovery, enrichment, integration and management of that data, allowing data to be quickly found, leveraged and protected, thus producing sound analytics.

Fluid and hybrid architecture 









Next to join this rapidly strengthening team is fluid and hybrid architecture. Fluid and hybrid capabilities help reduce costs even in an increasingly complex business environment. They allow analytics to be performed in ways suiting a company’s specific needs, whether by blending on-premise and on-cloud solutions into a compelling hybrid option or using adaptable data access without moving data.

An open and unified approach










Rounding out the team is an open and unified approach, which involves using solutions from a company that actively integrates open-source technologies into its offerings and that contributes to open-source initiatives. Using an open and unified approach greatly mitigates the risk of vendor lock-in and brings with it the benefits offered by technology that has been designed—and that is supported—by multiple people.

Building a base for your superteam

All four critical success factors must be in place if you hope to set up your ideal analytics system—which is why IBM is working hard to make sure that its analytics platform addresses each. The IBM analytics platform includes a variety of broad and deep offerings, such as Watson Analytics, which is well-suited for business users. In addition, IBM continues to provide high-quality data integration and governance to improve data quality. IBM is also pushing forward to deliver hybrid and fluid offerings. Topping it all off, IBM promotes an open and unified approach, particularly through its strong backing of Spark and its leadership role in the Open Data Platform initiative.

But these descriptions offer just a taste of what IBM can offer. In blogs to come, we’ll take an even deeper look at these critical success factors and learn how IBM addresses each. Keep an eye out, too, for blogs dealing with individual capabilities. After we’ve covered all topics at hand, stay tuned for the last post in this series, which will look to the Insight 2015 conference and describe how you can learn more about IBM’s analytics platform while attending.

Stay tuned for future posts, and check out the IBM analytics platform to learn more about how it addresses the four critical success factors.