By Bullett Manale, vice president of sales engineering, Idera
Five years ago we lived in a simpler world when it came to data. The majority of data used for analytics was stored in a SQL database and easily queried to provide insight. This simplicity has become a thing of the past. The type of analytics that companies want to do today – machine learning, data science, etc. – and the volume, velocity and variety of data highlights the need to let go of traditional IT environments and infrastructures. Today, departments have multiple databases, a variety of data streams and faster turn-around times for delivering critical business insight. The companies that can succeed with turning around the best insights the fastest, are the ones that will thrive in the Information Era.
In response to this, businesses are embarking on digital transformation and infrastructure modernization projects. The core of these projects include a cloud data infrastructure. Utilizing cloud-computing can help mitigate the rising costs of data storage, provide greater elasticity and enable wider access for data sharing.
However, cloud environments don’t build themselves. There are IT teams who try to build the entire operation from ground zero. While it is possible, this process is laborious, error-prone and riddled with data governance and management concerns if done incorrectly. So, what’s the solution?
Alongside the surge in data volume, formats and requirements, there has been a second, quieter evolution in automation. Automation is no longer just a way to generate fragments of code. It’s become an essential tool to an IT team’s arsenal when facing the ever-changing data landscape, answering the increasing business urgency for analytics and adapting faster than the competition.
At one point, professionals needed to evangelize automation and the depth of its potential. Now, its benefits are being revealed in various data infrastructure automation projects. From development through deployment and operation, automation can support the full lifecycle of data management.
With automation, we’ve seen customers significantly speed up their design and implementation efforts for data warehouses. This has enabled them to deliver faster time to value for businesses, even in the face of changing data sources, increased business needs and different types of data such as streaming data. As data usage regulation increases, automation can guarantee that supporting metadata and other documentation are current and accurate.
It’s exciting to think about the future following the adoption and implementation of automation. In a world where data volume, velocity and veracity continue to explode, automation is the essential building block of all infrastructure projects. In order to survive and thrive in the era of information, businesses need to fully leverage their greatest asset – data.
About the author:
Bullett Manale is the vice president of sales engineering at Idera, which recently acquired data automation company WhereScape.
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