DataOps Platforms Statistics

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Dataops Platforms Statistics 2023: Facts about Dataops Platforms outlines the context of what’s happening in the tech world.

LLCBuddy editorial team did hours of research, collected all important statistics on Dataops Platforms, and shared those on this page. Our editorial team proofread these to make the data as accurate as possible. We believe you don’t need to check any other resources on the web for the same. You should get everything here only 🙂

Are you planning to form an LLC? Maybe for educational purposes, business research, or personal curiosity, whatever the reason is – it’s always a good idea to gather more information about tech topics like this.

How much of an impact will Dataops Platforms Statistics have on your day-to-day? or the day-to-day of your LLC Business? How much does it matter directly or indirectly? You should get answers to all your questions here.

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Top Dataops Platforms Statistics 2023

☰ Use “CTRL+F” to quickly find statistics. There are total 8 Dataops Platforms Statistics on this page 🙂

Dataops Platforms “Latest” Statistics

  • Gartner predicts that by 2023, 70% of organizations will use value stream management to improve processes in the DevOps [or DataOps] pipeline to deliver faster value to customers.[1]
  • At least 80% of the business value of a modern data platform is delivered through change over time, not based on initial requirements.[1]
  • IDC research predicts that by 2020 we will have 44 GB of data worldwide, up from 3 exabytes in 1986.[2]
  • Only 17 percent of the 2,197 CIOs interviewed for the DataOps study felt that the strategic impact of DevOps on their organization was much less than that of big data (41 percent) and public cloud infrastructure-as-a-service (39 percent).[1]
  • Data volume on the internet is expected to grow at a CAGR of 32% to 180 zettabytes by 2025.[1]
  • The amount of data on the Internet is expected to grow at a compound annual growth rate of 32% to 180 terabytes by 2025.[1]
  • According to Gartner’s 2021 paper, “Evaluating Data Warehouse Automation Opportunities,” Xpert BI software was used as a case study to demonstrate that data warehouse automation can simplify DataOps implementations.[1]
  • IDC research shows that by 2023, 60% of organizations will have started implementing industrial DataOps solutions.[3]

Also Read

How Useful is Dataops Platforms

One of the main benefits of DataOps platforms is their ability to provide a centralized and automated way of managing data. Traditionally, data management has been a complex and time-consuming process, involving multiple steps and manual interventions. DataOps platforms aim to simplify this process by automating repetitive tasks, such as data collection, cleaning, and transformation. By doing so, these platforms help save time and reduce the risk of errors in data management.

Moreover, DataOps platforms promote collaboration among different teams within an organization. Data is no longer the sole province of data analysts or data engineers; rather, it is becoming a shared resource that can benefit multiple departments. With DataOps platforms, users from various departments can access and analyze data in a controlled and secure manner. This promotes cross-departmental collaboration and helps break down silos that can impede efficient data management.

Another advantage of DataOps platforms is their ability to improve data quality and accuracy. In the age of big data, ensuring the quality of data is paramount. DataOps platforms come with built-in features that help monitor data quality, identify anomalies, and take corrective actions. By maintaining high data quality standards, organizations can make more informed decisions and derive better insights from their data.

Furthermore, DataOps platforms enable organizations to scale their data operations efficiently. As businesses grow and their data needs expand, they need a scalable solution that can keep up with the increasing demand for data processing and analysis. DataOps platforms offer scalability features that allow organizations to adjust their data operations according to their changing needs. This ensures that organizations can continue to leverage their data effectively, regardless of how large or complex their data sets become.

In conclusion, DataOps platforms are incredibly useful tools for organizations looking to streamline their data operations and extract more value from their data. These platforms help automate manual tasks, promote collaboration among different teams, improve data quality, and enable scalability. While adopting a DataOps platform may require initial investment and training, the long-term benefits far outweigh the costs. By embracing DataOps platforms, organizations can position themselves for success in the data-driven world of today and tomorrow.


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