DataOps: Still an unsolved challenge for many organizations

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In our digital age, everyone understands the importance of data – gathering information, sharing it across the organization, and taking advantage of it to drive mission-critical decisions. Yet many organizations still have no handle on how to do those things well and fast enough. The unfortunate reality is that some valuable data is never shared with the right people at the right time. Worst of all, decision makers cannot always be sure that the data they rely on is accurate and up-to-date.

It is possible to build new technological processes and shape cultural expectations to successfully manage data. In fact, the software world has already achieved that goal through its development processes, and today it can be considered as a model for Dataps. Data managers are just beginning to increase their “productivity” to the same high level of organization, quality and trust.

A uniquely valuable asset

Data in 21 is the “driver of growth and change”st Century, as oil was 100 years ago Economist Writes – and it is just as valuable. “The flow of data has created new infrastructure, new businesses, new monopolies, new politics and – decisively – new economics.”

In the data-driven world, everyone recognizes that data is no longer just a by-product of major business processes, but a major asset with its own unique value. Every business, in every industry, can use its data to find new customers and retain customers, improve the brand experience for customers, study sales trends and refine marketing strategies.

But not every business today is making full use of its data. According to the Deloitte Analytics survey, data management in particular is lagging behind by three common challenges:

  • Low-quality data (only 34% of survey participants rated data as “excellent” or “good”, defined as integrated, accurate, and centralized)
  • Lack of analytics technology (49% had only basic reporting tools and limited predictive analytics tools)
  • Data ownership “power conflicts,” attributed to inadequate executive leadership (38% reported local analysis with limited sharing of tools, data, and people; 20% reported “unorganized pockets” of analytical efforts)

Nevertheless, 49% of participants agreed that the analyzes improved their decision-making ability. “Basically, analysis is about making good business decisions,” an analytics director told Deloitte. “There is no point in reporting just with numbers. We need to inform our decision makers in the best way possible. ”

Finding balance in a flood of data

Organizations are overwhelmed by the “flood of data” flowing towards them every day. The burden of data management falls largely on IT teams and specialized data teams, who are usually the only employees trained to analyze data. The learning curve is long and slow even when new experts come on board to motivate the team.

It doesn’t help that teams aren’t integrated, nor the data they use. The information comes from many sources, which are not always easy to trace and end up in multiple silos. Different teams manage pieces of data without any coherent processes, using different tools. The simple need for better tools all around complicates the effort. Sometimes it seems like the data just disappears into an incredible black hole.

Indeed insight-driven businesses – which make decisions based on data – remain in the minority today, according to the Deloitte Survey, and are “the most common criminal culture.” The study concludes that “it is not difficult to buy and use analysis tools – behavior change.” The most fundamental change is the “democratization” of data, which means training a wide range of employees in analysis, and equipping them with tools that non-technical people can effectively manage.

For the data manager, it is important to find the right balance between changing technology and changing culture. It’s also hard to do. A Forrester research study found that 88% of people are “ignoring their technology and processes or culture and skills – or both.” Only 12% say they have achieved an efficient balance between culture and technology and have learned to focus on both. Forrester calls these rare organizations “data champions.”

What do the best deals look like?

As defined in Gartner Vocabulary, Dataps introduces collaborative data management across the organization to improve “communication, integration and data flow between data managers and data users”. Dataps automate the design, deployment, and management of data delivery in a “dynamic environment” using metadata to enhance the value and usefulness of data. By ensuring “predictable delivery and change management of data, data models, and related artifacts,” DataOps promises to initiate best practices almost naturally.

Organizations can get more value out of their data by adopting advanced data lineage platforms, which can provide an automated, in-depth, multi-dimensional view of data travel. This allows data managers – and other users, from executives to front lines – a high level of visibility in the data flow, with the ability to map where data is coming from and where it is going, all the way from the original source to the reporting and analysis. Type Generation uses automated and augmented methods to create a comprehensive cross-system view of all the organization’s data, regardless of whether it resides in any silo, including all data flows and dependencies.

And, perhaps most notably, the Data Generation solution gives everyone the power to become their own data expert. Anyone can view the entire data landscape on a single screen, drag data from any source onto an automated platform, and do it manually, without the help of IT or data experts. This responds by integrating multiple teams with new tools working for each and integrating data on a transparent, reliable platform. Data teams also get the added benefit – independence from repetitive manual tasks.

A source of truth

Enterprises today may be overwhelmed by data, but they want it to keep coming. Forrester reports that the “thirst for data” among data-based decision makers continues to grow, even as they struggle to absorb their data. “Seventy percent of data decision makers are collecting data faster than they can analyze and use it, yet 67% say they consistently need more data than their current capabilities.”

Add to that the familiar fact that the “cost of poor data” costs the world $ 3.1 trillion per year, and it’s not hard to imagine why companies are thinking about datopops, and fast tracking the path to best practices. It all depends on whether one can establish a source of truth in the enterprise. That means the data that any team wants is always there, always clear and always reliable વગર without any more black holes.

And it’s good to remember that we have the means to become data-driven, insight-driven ventures across all teams and efforts, from top to bottom.

Yale Ben Erie is the CEO of Octopus,

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