The amount of data enterprise businesses are producing is growing by 40 to 60% a year, and many companies are facing challenges managing, analyzing, and interpreting all that data so they can enable solutions, support their data-focused teams, and glean valuable business insights.

1. What Is DataOps?
When Agile Meets
Data Analytics

2. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Title
Text
Introduction
Introduction
The amount of data enterprise businesses are producing is growing by 40 to 60% a year, and many
companies are facing challenges managing, analyzing, and interpreting all that data so they can
enable solutions, support their data-focused teams, and glean valuable business insights.
With requirements changing every day and the need for data access continuing to grow, many
organizations have to find ways to improve their data management processes.
That’s where DataOps (data operations) methodologies come in.
What Is DataOps? When Agile Meets Data
Analytics

3. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
What Is DataOps?
DataOps is an agile operations methodology that improves a company’s use of
data through better tools, automation, and collaboration.
The primary purpose of DataOps is to align data management tools and
processes with data goals, and improve communication and integration
between data managers and the end-users who consume data.
In a nutshell, DataOps borrows the principles of DevOps – an approach to more
agile and collaborative software development to speed up build lifecycles – and
applies those principles and processes to data analytics.

4. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
What Is DataOps?
DataOps encourages improvement and innovation by introducing the concepts
of agile development into the world of data analytics, so data teams and the
users who work with data can collaborate effectively to create a smooth, hassle-
free data pipeline.
Deploying DataOps improves the speed and accuracy of data analytics across a
company – including data quality, access to data, automation, integration, and
development and deployment of data products and applications.
DataOps practitioners, who can come from a number of different departments,
engage with teams of data scientists, analysts, engineers, and developers to
create cross-functional collaboration and increase the pace of their data-driven
deployments and initiatives.

5. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
The Biggest Benefits Of DataOps
● DataOps methodologies lead to better, cleaner data, which leads to improved analysis
and business insights.
● Improving collaboration between different parts of the technical team – including
engineers and data scientists – helps companies access and leverage data better, in far
less time.
● Organizations that take an agile approach to data science are four times more likely to
hit their financial goals.
● DataOps makes data more manageable and accessible for its biggest users. Many
times, these users are data scientists or analysts who are not as technically savvy as
engineers, and they need tools and processes for getting the data they need as
efficiently as possible so they can focus on their primary jobs.
● Creation and management of central repositories for application data and data models
allow for more detailed layers of analytics for organizations.
● Companies that deploy DataOps can reduce the cost of data management.

6. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
DataOps Helps Leaders Deliver Data Insights Faster and
Better
Effective deployment of DataOps gives teams a more agile, collaborative,
efficient approach to managing and automating the flow of data, so
stakeholders can get the data they need, when they need it, in a way that works
for them.
As companies ease into democratizing their data and giving users more self-
service ways to get data without needing to involve IT or engineering teams, I
predict that more and more companies will deploy DataOps methodologies to
keep things running smoothly and optimize their data analytics processes as
much as possible.

7. Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2020 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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