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Data Management Trends in 2023

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In a world driven by data, companies that are successful at extracting actionable insights through Data Management will be able to innovate more quickly, develop better strategies, and govern change more efficiently. 

Data analytics, which has been completely overtaken by technologies like artificial intelligence (AI) and machine learning (ML), has emerged as a critical game changer, and in the coming years, this perception will grow. Instead of big data, the new data analytics trend that has emerged is “right data” analytics.

Data Management Trends to Watch in 2023

  • The year 2023 will help successfully digitized businesses stand out – through their enterprise Data Management and Data Governance strategies. These successful organizations will get a chance to showcase their digitization blueprints, which are nothing but solid Data Management practices across their operations. 
  • According to Boston Digital, investing in tools that improve the customer experience will help enhance the digital footprint and ROI.
  • Single dashboards enabling data discovery, metadata management, and access to all data are high on enterprise wish lists. 
  • Gartner estimates that by 2025, more than “95% of new digital workloads will be deployed on cloud-native platforms.” 
  • The 2022 market for data integration tools has been driven by requirements around hybrid and multicloud data, augmented Data Management, and data fabric. This trend is likely to continue in 2023.
  • To remain flexible throughout their Data Management journeys, many organizations are using a mix of cloud providers’ best-fit capabilities – one cloud service for governing data science, and another one for governing applications.
  • Intelligent automation, personalized technologies, and customer-driven insights are all welcome trends for businesses. Tools that help manage customer data provide an opportunity for implementing intelligent automation.
  • In 2023, developments in disruptive technologies like AI, Internet of Things (IoT), and virtual and augmented reality (VR/AR) 5G will continue.
  • The digital business ecosystem will inspire start-ups, small to medium-sized enterprises, and larger organizations to use data analytics to improve the customer experience, lower costs, optimize existing processes, and engage with larger audiences. 
  • The success of human resources management (HRM) will be heavily dependent on data and the digitization of businesses in 2023 and beyond. In 2023, HRM software will take the lead in talent acquisition and talent retention processes. 
  • Lastly, staying ahead of the rapidly changing pace of technology will be essential in 2023. As enterprises try to ensure that they are building data-savvy and technology-savvy workforces needed for success going forward, the digital learning space will witness a growing adoption of gamification and VR into the employee learning process.

Data Governance Management in 2023 and Beyond 

Since nearly every enterprise, regardless of size, is collecting data these days, it makes sense to manage this data better to ensure better insights. This is where Data Governance comes into the picture, since this is most likely going to become a core part of service delivery processes in 2023.

Some of the biggest trends driving the market for Data Governance in 2022 are aimed at gaining competitive advantage in a volatile, “post-pandemic” business world. Here are the primary trends visible in the realm of Data Governance for the coming year:

  • With more data flowing to businesses, automation of Data Governance (DG) processes is high in demand. Also, data migration to the cloud will require business leaders to deploy sophisticated Data Governance strategies and technologies.
  • Thanks to the advancements in cloud platforms, organizations can now monitor and analyze volumes of enterprise data in real time, and take the necessary Data Governance steps when needed.
  • Learning and applying trends for Master Data Management (MDM) at an early stage will help organizations rise above the competition, cut costs incurred due to Data Quality issues, and gain insights more quickly. 
  • The rising importance of compliance will encourage organizations to embrace automated MDM tools. Thus, adopting and implementing AI-driven MDM solutions will be a critical enterprise function in 2023.
  • Automated MDM tools will dominate 2023 and beyond as these technologies become more adept at analyzing, connecting, cleansing, and discovering entities like customers and products. 
  • As more companies continue to adopt remote or hybrid working policy, self-service (automated) Data Governance will gain traction among the employees.
  • Organizations, over time, will be forced to discover and deploy more cloud-based Data Governance solutions to enable their in-house staff to manage data on their own without any support from IT departments.
  • Intercloud technologies will enable diverse Data Governance systems to seamlessly collaborate using cloud services running across cloud ecosystems. 
  • By tapping specialized AI- and ML-powered data services, even small, under-resourced data teams can deploy Data Governance and integration solutions on demand –automated data pipelines, automated Data Quality management, and automated Data Governance.

Role of AI and ML in Upcoming Data Management Trends

Automation in Data Management not only empowers ordinary business users to perform complex data-related tasks on their own, but also ensures that all regulatory requirements are met. Thus, the increased use of AI and ML solutions and tools has become necessary for businesses to remain relevant and compliant in an increasingly regulated Data Management ecosystem. 

  • Increasingly, studies about natural disasters such as earthquakes will rely on AI-, RPA-, and ML-powered big data for actionable predictions. 
  • AI and ML will take full control of big data gushing out of data centers – attempting to capture hidden relationships, and keeping and projecting insights in human-understanding boundaries. 
  • With global vendors engaged in a neck-to-neck race to launch transformational AI and ML solutions, organizations now will have a wider choice of available solutions. However, a wide choice of technologies and tools will also put business leaders and decision-makers in a dilemma to make the best choice to suit their needs.
  • The AI technology revolution will create new opportunities in data analytics in 2023 and beyond.
  • The sudden rise of automation in data analytics will necessitate businesses to automate as many processes as possible using AI, ML, low-code, no-code tools, and more options.
  • Tools that assist in managing customer data also create opportunities for implementing intelligent automation, which is another AI trend to watch out for.
  • Automation supports agile creation, management, and shutdown of data pipelines, giving organizations of any size or growth stage the data visibility they require within the Continuous Integration, Continuous Deployment (CICD) framework. 
  • By 2025, AI-driven, “context-aware” analytics models will replace 60% of existing models built on conventional data. 

Finally, the business staff can appropriately integrate these AI and ML solutions into their business processes to leverage organizational data capabilities for making efficient decisions, for analyzing ongoing trends, and for clearly identifying key competitive advantages.

Conclusion

Enterprises will continue to face increasing pressure to adopt advanced Data Management strategies to extract actionable insights from a tsunami of data in everyday business operations. 

This market pressure will force enterprises to make effective Data Management a top priority. 

In the next three to five years, more technologies and tools will emerge to support not just the Data Science and engineering departments, but also the underrepresented, data-centric departments such as sourcing, management, and corporate units. New skills like managing and analyzing unstructured data within data lakes will be critical over the coming years.

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