Many big firms such as eBay, LinkedIn and Google have been centered in Big Data from inception, thereby alleviating the need to consolidate or reconcile their Big Data with more traditional sources of data or their analytics. But many other large, established organizations and enterprises have had to find a way to integrate Big Data with existing, traditional IT infrastructures because current systems for Big Data management simply didn’t exist.
As a result, the CIOs of those organizations have had to “grow” their current information technology structures to accommodate Big Data storage, analytics and technology architectures.
The executives that are responsible for decision making about Big Data initiatives are making their approach in different ways, depending on their perspective on Big Data. For example, some organizations are looking at establishing Big Data capabilities for the first time while older, established organizations are really just concerned with doing what they were doing before only cheaper, faster and more efficiently.
Regardless of their approach, however, as prescriptive analytical models become fixed into key operational procedures, someone has to bring about the necessary changes in roles, process designs and skills.
In terms of skill set, the majority of larger organizations are attempting to augment their existing analytics staff with data scientists that have higher levels of IT competencies. Specifically, they must have the capability to manipulate Big Data technologies since traditional quantitative analysis is no longer enough; data scientists must work alongside quantitative analysts.
Since many CIOs question the ability of data scientists to possess analytics skills, many are taking a team-based approach. Team members likely possess skills such as natural language processing, text mining, image or video analytics and visual analytics. Data scientists also must be able to code in scripting languages such as Python, Pig and Hive. As far as background, many have Ph.D.s in science while others are just very good programmers with some analytics skills.
Another key skill that CIOs are finding imperative involves clarifying Big Data outcomes for executives by using visual displays or verbal narrative. Quantitative data needs to tell a story that resonates for decision makers.
Data-savvy leadership consists of building teams, making decisions regarding infrastructure based on existing information ecosystems, and excellent communication skills that bridge the divide between IT and business.
A Big Data-savvy CIO has to be able to ask and answer questions such as:
- What is the main set of issues and can Big Data help?
- What existing technologies will be integrated?
- Does the organization have the right skill sets in place to grow and customize Big Data solutions that fit the current as well as future needs of the business?
- Do new Big Data solutions need to communicate with incumbent platforms, and will the current IT department be able to facilitate that?
- Are there open source projects that may assist in getting started or growing in that direction?
- Is acquiring Big Data enabling technologies all at once practical, or should an alternative approach be considered?
- Under the assumption that acquisition tiers can be established, what are the corresponding budget tiers?
By circumscribing a select set of business issues, CIOs that are working on Big Data implementation can be more specific about the corresponding functional capabilities needed to help address them.
Regardless of whether it is a need for proof of concept, exploration of preliminary data or convincing executives to invest, CIOs often have to prove the value of Big Data technologies as a beginning step or more expansive delivery. This often signifies conveying cost efficiencies or economies of scale inside of existing business paradigms.
The skills, processes and tools needed to manage ever-expanding amounts of standard and non-standard data points will become increasingly important. CIOs with their eye on the future are continually working to build their skill set and expand their own capabilities as well as that of their teams.
Francesca Krihely is the community marketing manager for MongoDB, the leading NoSQL database. In this role she supports MongoDB community leaders around the globe.