Jul 10 2014

Can Analysts become Data Scientists?

Gartner believes big data will revolutionize the cyber-security domain in the next 2 years, but this transformation is at risk if the industry cannot find cost-effective ways to give their employees the capability to take advantage of that data. The Cloud Times notes there is a lack of data scientists who also specialize in security: “while security solutions are emerging prepared for the big data, security teams may not. Data analysis is an area where internal knowledge of the staff may be lacking. The data scientists who specialize in security are few, and will continue to be in high demand. As a result, it is likely that many organizations will turn to external partners to compensate for the lack of skills of internal analysis.”

There have been many articles written around the skill set of a data scientist, but we like what this post from Data Science Central had to say on the topic. There are 3 main skill sets, or pillars, that make up a data scientist:

  • Ability to hack/code;datasc
  • Strong mathematical/statistical knowledge; and
  • Domain expertise

An individual might be stronger or weaker in these three areas depending on the specific problem, which is exactly the case described in the Cloud Times article.  The cyber security industry has no lack of individuals with strong domain expertise, but individuals with the coding and math skills who specialize in that domain are rare and in high demand.  Even if they are found, how much risk is this putting on your organization? What happens if they get hired away? What happens to all that knowledge? Turning to external partners is a possible solution however, locating the right partner with the appropriate skills can be time consuming and not to mention, very expensive.

Instead of searching high and low for these people, consider empowering your existing staff of analysts, with domain expertise, to become proficient in the other two pillars, helping them emerge as a data scientist.

This is what IKANOW does. We empower analysts who may not have much, or any, coding or statistics experience to take advantage of the power of big data just like a data scientist.

Go from Analyst…


…to Data Scientist, with IKANOW


How do we do this?

  1. We empower our end users to connect / ingest various data sources with little, or no, IT involvement. Bringing in log files, social media, PDFs, web, excel, database, existing applications, and other data sources together in one platform previously required a great deal of IT involvement and coding. No longer with IKANOW.

  2. We allow end users to run complex queries and algorithms on data that is stored in MongoDB and Hadoop. You don’t need a data science or computer science background to query and analyze this data. We can also integrate our platform with other tools your team may be used to using.

  3. Analysts can analyze and visualize this data quickly and easily. No need to jump between multiple applications. You are able to gain the insights needed to make critical decisions with a few clicks of a mouse instead of running multiple, complex scripts.

Going back the data scientist description from earlier, our platform provides the most value for analyst in the mathematical/statistical skill set and we also lower the threshold for the hacking/coding skill set. This means your analysts, with domain expertise, become more like data scientists by drastically improving their hacking and mathematical skills.

To see if IKANOW is right for your organization, click on the buttons below to learn more.

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Ikanow Editorial

Press releases and articles from the Ikanow Editorial Team.