There is a new game in town.
It’s called the “Data First” movement.
But what does it mean, really?
On June 2015, there was an article published in Wall Street Journal that explains this movement quite well.
“Having spent many years as a firsthand practitioner on both the technology and the business side of the data fence, I can attest to how difficult it is to manage data well, and how frustrating it sometimes can be to be dependent upon the IT organization and the data warehouse for access. Can’t we just do it ourselves? Give us the data!”
This is the problem to begin with: too often the data in companies is isolated from everyday operations. This creates challenges for people, whose decisions are reliant on data, as they have to wait fairly long to get access to the data they need.
“The question facing many organizations today is how to integrate newly developed Big Data architectural approaches into traditional legacy data environments.”
This indeed is the challenge. It’s understandable that past decisions about data architectures were made with certain benefits in mind (and quite often those decisions did indeed lead to several benefits, when contrasted with previous models.) However, now those past decisions have turned into anchors for many companies, and courage to change them is needed.
Here are what Randy Dean sees are the core principles of Data First movement:
Businesses must have greater control over their data assets.
“The argument is that in the same way that the Internet has driven end-customer self-service, Big Data can drive business analyst self-service. The times demand it. Victory goes to the fast and nimble.”
Data discovery must be encouraged, and not penalized.
“Many of the most innovative firms have prospered by their ability to develop new products and services quickly, and validate them in the market. They have developed test-and-learn models which enable rapid analysis. In the past I have discussed the ability of leading edge firms to develop learning practices that enables them to “fail fast” and adapt quickly.”
Data efforts must move toward decentralization of control.
“The pendulum swings between the benefits of centralization and organizational control, and decentralization and unit autonomy. New approaches aim to enable greater responsiveness to data discovery while ensuring lightweight data governance standards to maintain data integrity at a corporate level.”
Inexpensive data storage and processing power have liberated data.
“Data can now be produced liberally and cost-effectively. Each data user is able to house and manage their own data environment. Data needs can be driven on-demand in the context of what information is required in the moment. Moving control of data to the business user means moving decision making closer to the customer.”
It’s been our experience as well, that “Data discovery must be encouraged, not penalized”, if any kind of meaningful results from data are to be expected.
The problem has been both cultural and technological up to this point.
But not anymore.
We have just recently launched a Discovery Analytics Service, which enables you to gain greater control over your data assets, and create a responsive environment, where you can quickly make better decisions based on actual data.
We invite you to read through our newly published datasheet on Discovery Analytics Service. It’s only 2 pages long, but gives you all the essentials in less than 5 minutes.
PS: The NDBS2015 is happening today in Helsinki (Kaapelitehdas). If you are there, come say hello to us at the booth E18.
COO, Service Delivery
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