Data Analytics has become a relevant part of how a modern organization can achieve the best insights from the available information and drive an efficient decision-making process.
If your company is going through a digital transformation is good to know the most important accelerators and enablers for Data Analytics.
Organizational approach
A data analytics project springs from a specific need or a specific issue to solve. It could be the Marketing Department that wants to design a new product given the clients’ unspoken needs or it could be the financial controller that wants to better understand which initiative creates more value. In any case, data are needed, analytical skills are involved and the IT department is called to help.
However, in a modern organisation, the weight of digital transformation could not be only on IT shoulders. Everyone should do her/his part.
Some projects (usually a small part) will need high-level competencies which could not be still affordable for all the companies (such as deep learning experts with years of experience in different fields) but others could be handled in-house with the resources already available and making the most with the great knowledge of the problem to tackle.
Moreover, the IT department is every day more involved in managing the demand coming from all the company departments. A new project (even a small one) should be planned in advance and a budget should be defined and approved. From my experience, an IT department could not afford any more the time-to-market needed by the business, apart from the rare cases of very high priority projects. Especially in periods like this one where budgets are everyday tighter.
That is why every department should invest in analytical skills and carry on projects with their own resources (with IT support at a minimum). People with an operational role in the project should have a general knowledge of how databases are structured and how to query them with a data visualization tool (like Tableau, QlikView, or Power BI to name a few), if not with some basic SQL.
#data-lake #analytics #version-control-system #business #data-science