Why big data analytics is at the heart of digital transformation

Marco Pozzoni

All of these applications have one thing in common: they require big data analytics. By 2020, IDC is predicting that 50% of the G2000 companies will see the majority of their business depend on their ability to create digitally enhanced products, services and experiences.

The channel is no different, and requires a data-first approach to manage the means in which distributers draw from consumer behaviour and sell products.

From analytics to action plan

Big data analytics is the heart of the digital transformation. It provides the ability to analyse data quickly and to transform it into an action plan, in order to get better insights, to take faster and more accurate decisions, and ultimately have a valuable competitive advantage. Advanced analysis grants businesses more of an insight into any organization and production processes, customers and markets.

For a successful digital transformation journey, channel partners need to establish new ways of leveraging and monetising on data. For that, data analytics need to be embedded in all new apps.
It is therefore not surprising that by 2019, 40% of IT projects will create new digital services and revenue streams that monetize on data. Data has indeed become the new currency of the digital economy.

What is analytics without storage?

While data analytics is the heart of the digital transformation, storage is the heart of any data analytics solution and here is why: high-performance storage ensures that analysis tools can access data quickly. A solid storage foundation is necessary for the success of any data analytics project.

If the foundation is shaky, the entire performance, security and, ultimately, the success of the project, will be affected. For this reason, it is worth paying special attention to storage - right from the start.

In order to exploit data fully, users need the ability to leverage data wherever it resides and apply analytics to it. Analytics tools such as Splunk provide an open platform that can access other data stores, including Hadoop and make data in Splunk available for accessing and sharing across the organisation. In order to realise top performance from Splunk – especially for ingesting and searching data quickly - you require a corresponding fast, available, scalable storage platform.