{"id":4896,"date":"2022-08-08T13:22:30","date_gmt":"2022-08-08T13:22:30","guid":{"rendered":"https:\/\/cms.idc-custom.solutions\/idcproduct\/grax-the-business-value-of-dataops-copy\/"},"modified":"2022-12-12T19:41:37","modified_gmt":"2022-12-12T19:41:37","slug":"grax-the-business-value-of-dataops-idc-demo","status":"publish","type":"idcproduct","link":"https:\/\/cms.idc-custom.com\/idcproduct\/grax-the-business-value-of-dataops-idc-demo\/","title":{"rendered":"GRAX – The Business Value of DataOps – IDC DEMO"},"content":{"rendered":"\n
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“DataOps is a new discipline but is catching on quickly because it reduces data errors and application errors and enhances the speed and quality of data, giving businesses a competitive edge”<\/p><\/h3>\n<\/div><\/div>\n\n\n\n

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What is DataOps, and what is its significance in helping organizations become intelligent digital businesses?<\/h2>\r\n\t\t\t\t<\/div>\r\n\t\t\t\t
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We are in a digital economy. By 2022, more than 65% of global products and services will come from digitally transformed organizations that are heavily reliant on data and data-native workers for business success. According to an IDC survey, 80% of CEOs emphasized that using data in advanced decision models for performance and competitive advantage is “extremely important” to their organizations. This is because they see a strong correlation between data-driven insights and business outcomes.<\/strong><\/p>\n

As the value of data and data-native workers grows within enterprises, many are turning to DataOps strategies to improve the outcomes of data analytics, data science, artificial intelligence (AI), and machine learning (ML).<\/p>\n

DataOps is a new discipline but is catching on quickly because it reduces data errors and application errors and enhances the speed and quality of data, giving businesses a competitive edge. According to IDC’s research, effective DataOps methods in use among enterprises today include data sandboxes, version control, feedback loops, and logic and data testing. As DataOps borrows the principles of agile and DevOps methodologies, it lends itself to data science, data visualization, and data warehousing use cases by breaking down the silos in data pipelines from ingestion to analysis and visualization. DataOps is a set of best practices enabled by platforms such as data-enabling backup platforms that help break down data silos.<\/p>\n

By 2023, 60% of organizations will start implementing DataOps programs to reduce the number of data and analytics errors by 80% and to boost trust in analytics outcomes and efficiency of data-native workers. The DataOps focus on quality will improve the level of trust in data, data analytics, and data science as it helps organizations adapt to new business needs.<\/p>\n

DataOps is not one tool but an entire pipeline made up of multiple tools and technologies that are connected or coordinated in DataOps processes. The key to success is to support more integrations and automate testing at various points within the data life cycle.<\/p>\n\t\t\t\t\t<\/div>\r\n\t\t\t\t<\/div>\r\n\t\t\t<\/div>\r\n\r\n\t\t\t\r\n<\/div>\r\n<\/div><\/div>\n\n\n\r\n<\/a>\n\n\n

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Where does valuable business data reside? How can businesses best capitalize on this data? <\/h2>\r\n\t\t\t\t<\/div>\r\n\t\t\t\t
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Data gravity is beginning to shift to the cloud as cloud is everywhere for everything.<\/strong><\/p>\n

Business data is growing at an exponential rate, and more organizations are having to manage petabyte-scale data. In fact, according to IDC’s research, twice as many organizations in 2021 admit to having petabyte-scale data compared with 2019. This data is fragmented across core datacenters, SaaS applications, cloud infrastructure, and edge locations.<\/p>\n

SaaS adoption is accelerating as these applications bring a modern UI, enable better collaboration, and transform legacy business processes. According to IDC research, mature business processes such as CRM, ERP, finance, HR, email, and collaboration are all predominantly becoming SaaS based. This in turn means that business-critical data such as sales, customer, marketing, and even financial data increasingly resides in SaaS applications.<\/p>\n

In conversations with IDC, more customers have said that they rely on data in Salesforce to inform their business road map, customer experience management, and marketing strategies. About 52% of large enterprises have customized or added development on CRM applications to meet their business needs, making data in SaaS CRM applications business critical and relevant for analytics outcomes.<\/p>\n

Multiple trends are colliding:<\/strong><\/p>\n