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Digital Transformation and Agile, Modern Data Architectures

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Digital Transformation and Agile, Modern Data Architectures

An industry executive talks about the need for more agile data operations and architectures, and how DataOps could hold the key.

· Big Data Zone ·
Free Resource

Digital transformation is one of those industry keywords that a lot of executives toss about but that most are not really sure really what – or how – their firms are doing to make it a reality. Rather, what executives need to be concerned about is how data is leveraged, as it is at the heart of enabling business transformation and change. Forrester reports that between 60-73 percent of all data in an enterprise goes unused for analytics. When data is recognized as the single most valuable asset for business growth, uncovering customer insights and driving decisions, that figure is no longer acceptable or cost-effective.

What keeps a company competitive and relevant to its customers and investors is how fast it can pivot to accommodate the changes in the economy and their industry. The news has been ripe with examples of companies who have struggled to keep up with the rapid pace of business and ended up claiming bankruptcy in 2018 including Toys R Us, Sears, Nine West, and others. And it all comes down to data and how it has changed the very fabric of business operations.

The speed at which companies operate has exponentially accelerated due to a world where real-time insights and fast decisions are critical. By exposing all the information for use in real-time, an organization has the agility to match its processes with the true realities of rapidly shifting markets and operate at that speed of change.

Thus, data is the driving force behind any digital transformation and it is the reason why enterprises require modern data architectures that are hybrid or cloud for greater efficiency, data lakes for increased scale, and streaming pipelines for real-time data movement. But as organizations move to modern architectures the challenge to get the data they need becomes clear.

At the core of these architectures is new, agile data integration technology that creates real-time data streams from core transactional systems and moves it to the cloud and data lakes and then processes the data to make it immediately ready for analytics, addressing the need for the right data at the right moment.

This innovative style of data integration technology and management practices is being termed 'DataOps.' Simply put, DataOps is a strategy that improves the communication, integration, automation, and use of data between executives, business users, and the IT/data teams. As a result, enterprises can advance the speed and accuracy of their analytics and improve overall productivity. It breaks down the data silos across the organization allowing for data to be moved and used while providing more information on the different source data collected. Companies will benefit from better business insights and a keen competitive edge – it will allow them to operate at the speed of change.

For any enterprise to remain viable and relevant in today’s rapidly changing world, executives need to move past using and worrying about buzzwords such as digital transformation and look to their data for inspiration and insight. It is here where those companies who use its information effectively will grow while those who keep with the antiquated methods of data operations will stagnate and fade away.

Topics:
dataops ,data integration ,digital transformation ,data analysis ,big data

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