Digital transformation is reshaping the way we do business across all industries. Already today, organizations are focusing on delivering new classes of applications, such as Internet of Things (IoT), Virtual Reality or Artificial Intelligence. All of these applications have one thing in common: they require big data analytics. 50% of the G2000 companies will see the majority of their business depend on their ability to create digitally-enhanced products, services and experiences by 2020 as per a latest report.

There are many sources that predict exponential data growth toward 2020 and beyond. Yet they are all in broad agreement that the size of the digital universe will double every two years at least, a 50-fold growth from 2010 to 2020. Human- and machine-generated data is experiencing an overall 10x faster growth rate than traditional business data, and machine data is increasing even more rapidly at 50x the growth rate.

The acquisition and analysis of data and its subsequent transformation into actionable insight is a complex workflow which extends beyond data centers, to the edge, and into the cloud in a seamless hybrid environment. Historically, data processing and analytics systems had specialized features for business analytics and high-performance computing workloads. Yet with the advent of big data and high performance computing, everything seems to be converging to high-performance data analytics.

Big data analytics is the heart of the digital transformation. It provides the ability to analyze 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, companies need to establish new ways of leveraging and monetizing on data. Data analytics need to be embedded in all new apps.

Let’s take an example of Oil & Gas upstream Industry.  The upstream industry has implemented several types of digital oil fields and smart field technologies, better known as digitization. Digitization is defined as the representation of an object, image, sound, document or analog signal by generating a series of numbers that describe a discrete set of its points or samples. The next phase of digital transformation is digitalization, defined by Gartner as “the use of digital technologies to change abusiness model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business.”

Digitalization makes use of emerging technologies such as cloud, big data analytics, mobility etc. to engage with stakeholders to address specific challenges and needs in a cost effective and efficient manner and hence enable business growth at an accelerated pace.

In the process of digital transformation, typical upstream industry will have around 700+ apps in addition to the structured data from enterprise applications.

If data generated is application centric, imagine how automatic sharing this data among various applications can be such a herculean task, almost impossible to accomplish. On top of it, if there is a merger or acquisition of another firm, it will be a big mess.

Hence organizations must have a solid data centric foundation and data governance in place, so that data from various applications can be seamlessly integrated and exchanged.  This is essential for performing real-time resource optimization, and increasing the growth of data formatted at the collection point for multiple applications instead of traditional way of data collected and stored for a single-use purpose. Data governance and data security framework are very important in order for digital transformation to succeed in any organization.

Successful CIOs are adopting a platform strategy that is based on the foundation of integration, agility and modularity. Expedien team of experts has been focused on helping its clients a solid data foundation with secure access to all the data, no matter where it sits, and ensuring it’s not only high quality, it is also reliable, trusted, in a format that can be used and reused; even for purposes we haven’t thought of yet. Successful companies are not only moving towards data excellence but also driving innovation leveraging big data analytics as a part of digital transformation.