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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 it can be considered as a model for dataps today. Data managers are just beginning to elevate their “product” to an equally high level of organization, quality and trust.

A uniquely valuable asset

Data in the 21st is the “driver of growth and change”St. Century, as oil was 100 years ago The 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 core asset with a unique value. Every business, in every industry, can use its data to find and retain new 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 is attributed to “power conflicts,” 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 must inform our decision makers in a way that suits them best. ”

Finding balance in a sample 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 – to change behaviors.” The most fundamental change is the “democratization” of data, which means training a wide range of employees in analysts, and equipping them with tools that non-technical people can effectively manage.

For data managers, 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 in 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 distribution and transformation management of data, data models, and related artifacts,” Dataps 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 અને and other users, from executives to front lines ઉચ્ચ high-level visibility in data flow, with the ability to map where data is coming from and where it is going, from the original source to reporting and analyzing this type of genealogy. Uses automated and augmented methods to create a comprehensive cross-system view of all of 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 to integrating multiple teams and integrating data on a transparent, reliable platform with new tools working for everyone. 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 “thirst for data” continues to grow among data-driven decision makers, 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 weak data” costs the world $ 3.1 trillion every year, and it’s not hard to imagine why companies are thinking about datopops, and fast tracking the path to best practices. All of this will depend very much on whether they can establish a source of truth in the entire enterprise. That means the data 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, from top to bottom, across all teams and efforts.

Yale Ben Erie is the CEO of Octopus.

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