Big data projects require a diverse team with varied skills. Beyond the basic IT skills you also need Hadoop and NoSQL programmers and experts to analyze the results. And since big data projects affect the entire organization, your interdisciplinary team needs to include representatives from the departments that will take advantage of the big data findings.
What this means for VARs is you have to be prepared to bring the right big data expertise to an interdisciplinary team, and you need to be prepared to enlist the right executives from your customer.
According to Gartner, 4.4 million jobs will be created by 2015 specifically to support big data projects, including 1.9 million jobs in the United States alone. However, finding the talent to fill those jobs continues to be a challenge. Gartner analysts note that when hiring you need experts who understand hybrid data, structured and unstructured data, and most important of all, analytics that will shed light on “dark data.”
So when assembling the team for big data projects, you need to inventory the expertise you have in-house, determine what expertise your customer has to offer, and identify the outside expertise you will need to contract to achieve a successful outcome.
What Expertise Do VARs Need to Bring to a Project?
For resellers, the objective is to bring the right personnel to support big data projects without having to rely extensively on outside experts. Most VARs have the IT talent to handle data storage, virtualization, and cloud computing, but that is only one aspect of big data staffing. You also need to find the data scientists and programmers who can design and implement Hadoop frameworks and extract insight from the analytics.
EMC solves the problem by training their in-house team. EMC executives estimate that 20 percent of their big data scientists are hired from outside and 80 percent are trained in-house. Hadoop skills are considered “table stakes” and are essential for any big data project. Rather than looking for data scientists who don’t exist or are too expensive, VARs would be better served finding in-house database experts familiar with SQL and NoSQL and training them in big data platforms like Hadoop.
These “data hunters” are the backbone of big data projects. They are able to assess data sources and build algorithms that can extract the information needed to deliver insight. In fact, EMC sends its big data analysts into customer sites as an advance party to assess needs, data sources, and the scope and nature of big data projects.
Everyone Has a Stake in Big Data
As part of the interdisciplinary team, you also need to get participation from all the stakeholders in big data projects. For example, if you are seeking insight into sales and marketing, participants from the sales and marketing departments need to be part of the team to make sure all the relevant data is applied and the outcome of the project has strategic value. Similarly, if big data is being used to optimize manufacturing, make sure you have representatives who understand the value chain and the production line to guide data gathering and assess the results.
Big data projects are about making better informed decisions, not about the data itself. Using an interdisciplinary approach that encompasses business, statistics, technology, and other areas means you not only target the right data sources to reveal trends but you have the interpretive skills to identify the underlying causes; you determine both the what and the why.
Insight Is All That Matters
To uncover the hidden meaning from big data projects, it’s useful to have vertical market expertise as well as analytical skills. The larger objective of big data is to deliver insight to make better business decisions. Understanding the factors behind those business decisions and the market dynamics is extremely valuable.
Having good interpersonal skills is also an asset. The big data team has to bring together different stakeholders with diverse backgrounds and get them to work as an interdisciplinary team. That requires the ability to empathize with the needs of stakeholders and translate their needs into parameters for the big data project.
And your team needs to have to be able to communicate its findings. This means more than delivering dry reports with spreadsheets. Findings have to be converted into charts and graphics that dramatize the findings and makes them relevant to the question being asked. If they don’t deliver insight, big data projects are a waste of time and money. The best way to deliver insight is with easy-to-understand graphics and bullet points that highlight relevant findings.
What skills to you see your team bringing to big data? Where can your team deliver the greatest value?