20 Predictions for a DataOps 2020

20 Predictions for a DataOps 2020: 20 Articles Predicting DataOps is the Next Big Thing in 2020

Here at DataKitchen, we’ve been promoting the ideas behind DataOps for many years. It is great to see so many influential organizations like Gartner, Eckerson, TDWI, and others predict that DataOps will take off in 2020. We’ve done a lot of Googling and came up with a list of 20 Articles predicting DataOps advancement in 2020. Happy New Year!

Eckerson Group’s Predictions for 2020

Prediction #6 – Lean, Agile and Product Management Approaches Go Mainstream

Digital transformation is disrupting every industry across the globe and business agility is now a business imperative. Enterprises must learn how to adapt quickly to increasingly rapid changes in technology and economic conditions to avoid extinction. Companies that embrace Lean, Agile, and DataOps development approaches and execute their analytics portfolio using a Product Management mindset will succeed.


Why DataOps is a Major Quality Trend for 2020

DataOps provides the opportunity to apply developer-proven disciplines as a quality check for data and associated programming.


8 Analytic Trends to Watch in 2020

Moreover, a wider scope of data type structures used for programmatic advertising requires methodologies to ensure that errors are not systematic, so developer-influenced methods like DataOps will be essential to maintaining data quality and preventing compliance mishaps.

As more enterprises develop AI pilots into production, IT leaders will need to deliver infrastructure stacks for DataOps, ModelOps and, most importantly, platforms that support the integration of streaming-data analytics into the enterprise architecture.


Why your organization needs to adopt a DataOps approach in 2020

I’m confident 2020 will be remembered as the year DataOps came of age, as companies are discovering the need to maximize the inherent business value of their data. DataOps adds the observations that are needed in all aspects of data management that keeps tracks of data moving at speed across the organization.


Gartner Predicts 2020: Artificial Intelligence Core Technologies

As more enterprises develop AI pilots into production, IT leaders will need to deliver infrastructure stacks for DataOps, ModelOps and, most importantly, platforms that support the integration of streaming-data analytics into the enterprise architecture. To enable scalable infrastructure strategies for putting AI into production, IT leaders should:

  • Curate DataOps ecosystems that simplify management, transformation and versioning of data, coupled with batch compute platforms for model training and evaluation.

  • Devise ModelOps ecosystems that enable versioning, reuse, rollback and deployment of ML models.

Getting AI into production requires IT leaders to complement DataOps and ModelOps with infrastructures that enable end users to embed trained models into streaming-data infrastructures to deliver continuous near-real-time predictions. As more enterprises embrace production AI, the need for and use of streaming-data analytics infrastructures will increase


Report: top analytics developments that took place in 2019

According to Christopher Bergh, “DataOps is the recognition that a set of problems have crept into organizations over time and slowed down productivity”. He further added that DataOps “encourages data-driven organizations, to begin with, a similar practice of testing their data pipelines to build trust and evolve best practices.”


Predictions for 2020: Trends leading the way for the next wave of digital transformation

Cloud migration has been gathering increasing momentum amongst enterprises in recent years – especially within DataOps. 


Advanced Analytics: A Look Back at 2019 and What’s Ahead for 2020

The Bottom Line In 2020, we’ll see even more technology advances made, but organizations will also address the practical aspects associated with utilizing advanced analytics and ML. They will determine whether they can improve the skills of their business analysts; evaluate whether they will be able to use some of the new tooling on the market; and realize that they need a DataOps team if they want to succeed in advanced analytics at scale.


Software predictions for 2020 from around the industry

DataOps will gain recognition in 2020: As organizations begin to scale in 2020 and beyond — and as their analytic ambitions grow — DataOps will be recognized as a concrete practice for overcoming the speed, fragmentation and pace of change associated with analyzing modern data. Already, the number of searches on Gartner for “DataOps” has tripled in 2019. 


Why 2020 is the Year You Will Manage Your Data as Code

Manage the Complexity of Data with DataOps

During application development, developers need to have accurate and portable data sets, so they can focus on writing accurate high-quality code instead of writing mocks. The same datasets should be portable and available to different pipeline phases, so tests run quickly and accurately.

In short, quality is dependent on testing with production-like data. Dev teams should be able to manage the cadence in which their datasets are updated and be able to receive updates without manual intervention through self-service controls. Reducing the friction between developers and those who manage and secure data is what DataOps is focused on.


Industry AI, Analytics, Machine Learning, Data Science Predictions for 2020

Vendors are entering the space with DataOps offerings, and a number of vendors are acquiring smaller companies to build out a discipline around data management. Finally, we’re seeing a number of DataOps job postings starting to pop up. All point to an emerging understanding of “DataOps” and recognition of its nomenclature, leading to the practice becoming something that data-driven organizations refer to by name.


8 Top Big Data Analytics Trends That Will Dominate 2020

The latest technological workflow to come up from the fields of IT and Big Data professionals are DataOps. It is not to be confused with DevOps. DataOps focuses on how to cultivate, manage, and process data with agility and accuracy so that end users can have insights quickly.


2020 Trends: Analytics Alone is No Longer Enough

DataOps + Analytic Self-Service Brings Data Agility Through-out the Organization

Self-service analytics has been on the agenda for a long time, and has brought answers closer to the business users, enabled by “modern BI” technology. That same agility hasn’t happened on the data management side – until now. “DataOps” has come onto the scene as an automated, process-oriented methodology aimed at improving the quality and reducing the cycle time of data management for analytics. It focuses on continuous delivery and does this by leveraging on-demand IT resources and automating test and deployment of data.


Going beyond Analytics – The trends enabling the data mosaic in 2020

DataOps and self-service spread across the information value chain

Modern BI delivers business users much closer to the insights they need through self-service analytics. However, until now that same model has alluded the data management side. The emergence of DataOps, a set of agile practices, processes and technologies for building and enhancing data and analytics pipelines, will help improve quality and reduce the data management cycle time.


20 Predictions for 2020 from AI to Data Management

DataOps emerges as not only a process but a platform


Top Big Data and Analytics Predictions for 2020

7. Dataops

The DataOps concept has gained ground in the year 2019 with the advent of more complex data pipelines that required more integration tools. DataOps involves both Agile and DevOps methods to the entire lifecycle of data analytics.


2020 DevOps Predictions

Data. DevOps and DataOps will converge! There’s so much data out there across all technologies and spaces, and we need to have better ways of managing it, collecting it, searching through it, and making it visible to others


What is the future of enterprise analytics? 14 game-changing trends for 2020

In the future, more business leaders will adopt data management tools like DataOps, a combination of DevOps and Agile methodologies, to align data with their business’ goals. It improves the quality of data management and reduces the cycle time in business operations.


15 Technology Predictions for 2020

Prediction: Organizations Will Embrace DataOps For More Collaborative Data Management

Why? DataOps is a methodology, like DevOps, that fosters collaboration, communication, integration and automation of data flows. It automates the design, deployment and management of data delivery, using metadata to improve the usability and value of data in a dynamic environment, according to Gartner. The results include reduced frustration, better data utilization, improved governance and faster time to market.


7 Data Trends for 2020

Move towards DataOps thinking. The ability to deliver value quickly, with robust processes and move data through the value chain – from idea to activation – is where organisations will win with data. Through 2020, we’ll see the growth of DataOps as a method to achieve this ambition.

Thinking about building data products and solutions with similar methods seen in digital native businesses and startups will increasingly be a focus.


Even CRN is predicting DataKitchen will be ‘one to watch’ in 2020. https://www.crn.com/slide-shows/applications-os/10-hot-big-data-companies-to-watch-in-2020/4

To learn more about how a DataOps Platform can help your data organization develop analytics at lightning speed and eliminate errors, contact us at www.datakitchen.io.

You can read more about DataOps by downloading “The DataOps Cookbook,” our free book explaining DataOps in detail and how you can get started immediately.

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