Actually I am the local Manager of the Data team for a huge consulting company. Theses companies structure their businesses and teams around specialized business unite which each has a dedicated scope of action. In this environment, one of my everyday tasks is to explain what "Data" stand for. In this article I'll talk about what someone working on the data field might really work on !

Everything is Data and Data is Everywhere !

Then I try to argue explaining that even if my particular unite have a specification in some tools our scope is really broad. I love to use actual BuzzWords such as "BigData",  "BlockChain" and "AI" to attract the attention but the real deal behind our title is mostly what we usually call "Analytics" or "Business Intelligence".

The three types of work

It quickly came to my mind that there is finally three types of work area that I (as a "data" worker) should be involved in.

First of all, we are mainly BI consultant from technical to business analyst working with multiple tools in multiple environments. The job took place in three steps:

  • Extract
  • Clean
  • Exploit

Well, there is obviously much more thing to do behind the hood like identification, consolidation, aggregation, give sense, but that is another story.

We mainly use ETL tools with relational databases (sometimes cubes) and BI platform for reporting.

This is what I call the traditional BI work which is institutional in companies and mostly used as global reporting tools.

The second type of work is where I put all of the fancy technical aspect of working with data. DLT, BigData, AI with what I call the "New BI".

More and more, companies have to deal with much more data even quicker. For that, employee now have/need to be more involved in the data of their companies. It means that they should access, manipulate and interpret the data by themselves. They need the tools we put in the "self-service BI" package.

All of these new needs are supported by:

  • BigData technic to be able to support the new volumes of data
  • AI that will create more value from the acquired data
  • DLT that provides a way to skip a centralized regulation in the transactions.

Finally, and I think this is where we have the more work to do: help company to be "Data Driven" company !

More consultancy than a delivery job, this is where we should use our brain the most. Some companies are already aware and already started their transformation. But for most companies they aren't aware of this new trend of being data driven. Today, the most powerful companies are the one who owns and uses the data. And it's not only true regarding tech companies. In every sector, the one who creates the biggest value from the data is the leader. How do you conquer new clients ? How do you keep your clients ? How do you optimize your performance ?

It all start with data.

To finally answer the question, I'll say that for a consulting company, working on the data mainly mean you are working around "data analytics". But for more personal orientation, you need to be open-minded and have a really broad knowledge on IT and economy.