Small Steps For Data Analytics
In the rapidly evolving IT space, the notion of creating and leveraging data analytics is rapidly gathering momentum, for the all right reasons, including the nature of the complex problems we are trying to solve, the volume of data we need to store and the velocity at which we need to process it to be able to create data models swiftly to answer our complex business questions in real time. For Einstein aptly said, “The solution of the problem cannot be the simpler than the problem itself.”
However, for a multitude of reasons, getting started on this journey remains challenging, where and how to undertake this big effort, being one of the biggest impediments toward its adoption. With the underlying technology, hardware and software, for data analytics reaching a new level of maturity, the strategic framework to formulate the journey is not as much a question of technology, or its underpinning elements, but rather of structural and systemic cross-functional elements that need to be aligned to ensure the journey is effective. On the outset, we will define effectiveness as the ability to achieve the intended business results within anticipated costs and timelines.
My goal here is to outline a conceptual framework that can help organizations and business units to plan and align the relevant stakeholders to maximize the success of data initiatives. I will also highlight the effort we undertook within Dell IT, with our strategically aligned business (SAB), to identify and leverage synergies in the efforts in data analytics during our first SAB Roundtable titled, “Driving Business Value with Data.” SABmembersarepubliccompaniesPivotal,VMwareandSecureWorks—allthreeofwhichhaveDellasamajorityshareholder—andDellinternalbusinessesBoomi,RSAandVirtustream.
Sir Arthur Conan Doyle, physician and author of the Sherlock Holmesbooks, once said, “It is a capital mistake to theorize before one has data.” To have data is important, but to be able to identify the relevant data sets and to be able to infer correctly is even more important. Your ability to identify relevant data and its inference is predicated on your ability to identity your key performance indicators (KPIs). Your destination, your business goals, your success criteria and your use cases are the first step toward their realization. To illustrate, if you ever have to ask the captain of the ship its destination, in a word or two, the captain will be able to tell not just the destination but will also be able to map out the journey for you.
In the data center, we are no different. The ability to define our goals from data analytics journey destination, including defining its success succinctly on quantifiable dimensions, is key and should be done with each of the business units that intends to pursue a data analytics solutions.
