One of the many consequences of the development of new, improved big data analytics technologiesRead More
How can companies take advantage of the ‘data first’ movement
One of the many consequences of the development of new, improved big data analytics technologies is that many businesses are starting to rethink how they manage their digital assets and use this information to transform their operations.
But as enterprises look to place data front and centre, they will face a range of challenges. Chief among these will be how they integrate their newly-developed big data approaches into existing data environments.
Writing in the Wall Street Journal, chief executive and managing partner of consultancy NewVantage Partners Randy Bean stated that the industry is changing fast, with many employees demanding a new approach in order to take full advantage of the potential offered by big data.
"With the growing and accelerating proliferation of data, some business users have begun to sound a drumbeat as they demand a more flexible and dynamic data environment that is responsive to their needs – and by extension, the needs of their end customers," he said.
In order to achieve this, Mr Bean highlighted several key areas that businesses must bear in mind if they are to successfully transition into a 'data first' enterprise.
For starters, companies must keep close control over their data assets, while at the same time ensuring that activities and ideas that use big data are encouraged and not penalised, even if they do not always succeed.
Mr Bean observed that this has enabled many innovative enterprises to develop new products and services quickly, and validate them in the market. By developing 'test-and-learn' models that enable rapid analysis of data, innovative businesses can ensure that they 'fail fast' and adapt quickly to improve their offerings.
Big data efforts must also encourage the decentralisation of information to give business units more autonomy, without compromising on issues such as data governance. This has been enabled by lower costs for storage and processing, that allow individual departments to take control of their own analytics operations.
"Data can now be produced liberally and cost-effectively. Each data user is able to house and manage their own data environment," said Mr Bean. "Data needs can be driven on-demand in the context of what information is required in the moment."