Industry executives and experts share their predictions for 2019. Read them in this 11th annual VMblog.com series exclusive.
Contributed by Dan Potter, VP Product Management and Marketing at Attunity
The Emergence of DataOps
2018 has shaped new
opportunities for the year to come. The exponential growth of data will continue
to have the biggest impact on enterprises and how they manage their businesses,
leaving firms open to improved technologies to solve their increasing data
challenges.
At Attunity we see three big
topics shaping the data landscape in 2019.
The rise of DataOps
The
race for processes that allow enterprises to capture
and manage constantly changing data across the organization has begun. 2019 will welcome a more collaborative data management
practice as enterprises try to integrate data in real time for better business
insights.
Although relatively new, DataOps will be key to improving communication,
integration and automation of data loads between
business analytics consumers and the data/IT teams. Consumers using a DataOps strategy will be able to advance the speed and accuracy of their analytics
and improve productivity. By leveraging
real-time integration technologies such as change data capture (CDC) and
streaming data pipelines, DataOps is disrupting how data is broadly shared and how
it is made available across the enterprise. Thanks to the increasing focus on
integration and automation, it will break the silos in IT operations. This will
allow organizations to move data at the speed of change while providing more information on the different source data collected. Companies will
benefit with better business insights and a keen competitive edge.
The cloud re-evolution
This
year focused on a mass data movement to the cloud, taking big steps to
consolidate analytics-ready data. Whether driven by hybrid environments or full
cloud strategies, the trend now is moving fast toward a hybrid and multi-cloud
approach.
As all public clouds are not created equal, enterprises will
increasingly invest in various cloud platforms that will respond to different
business requirements. We will continue to see a proliferation of
infrastructures, databases and analytic tools that address very different
functions - giving more flexibility to move and use the data. However, organizations will have to
face the challenge of bringing all the
information together for proper analysis.
Modern data integration
In
2019, enterprises will turn to modern data integration approaches that can automate
data pipelines to support modern analytics platforms, such as data lakes or cloud data warehousing.
In this context, IT leaders should take a deeper
look at their data integration architecture to ensure that it can keep pace
with rapidly changing infrastructure, data volumes, and business
requirements. Data lakes can bring immense value by decoupling the
storage from the compute and provisioning specific data sets to support
different analytic use cases. To overcome
the complexity, modern data integration pipelines support orchestration and
automation across the multi-step process of data ingest, transformation and
provisioning.
With the cloud, data
lakes, a wide variety of analytics engines and modern data integration
platforms at their service, enterprises will be able to analyze data at the
speed of change to stay relevant and competitive.
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About the Author
Dan Potter, VP Product Management and Marketing
at Attunity
A 20-year marketing veteran, Dan Potter is VP Product Management and
Marketing at Attunity. In this role, Dan is responsible for product roadmap
management, marketing and go-to-market strategies. He has also held prior roles
at Datawatch, where he was CMO, and IBM where he led the go-to-market strategy
for IBM's personal and workgroup analytics products. Dan has also held senior
roles at Oracle and Progress Software where he was responsible for identifying
and launching solutions across a variety of emerging markets including cloud
computing, real-time data streaming, federated data, and e-commerce.