Infogix’s Seven Biggest Data Trends to Watch in 2021


Posted December 8, 2020 by Connectcoms

Providing Business-Ready Data to a Remote Workforce and 3D Data Lineage Tops the List of What Businesses Must Know About ASAP

 
Naperville, Ill. – December 8, 2020 – Infogix, a leading provider of data solutions, debuted its annual list of transformative data trends businesses must prepare for in 2021.

Each year, Infogix’s global experts’ team pinpoints critical data challenges and growth opportunities data leaders will face in the new year. However, 2020 was an unprecedented year. The coronavirus pandemic has affected the way every trend will play out in 2021.

“When employees were thrust into remote work environments due to the pandemic, data-driven organizations were forced to rethink data processes and procedures,” said Emily Washington, executive vice president of product management at Infogix. “As we head into 2021, organizations are embracing data technologies that improve IT infrastructure and meet the evolving needs of data users.”

The following seven data trends will dominate 2021 and shape the future of business:

A Better Way of Solving Major Data Challenges of a Remote Workforce
More employees are working from home than ever before, increasing the need for on on-demand availability and access to data from remote locations. Pair that with heightened security and data privacy concerns that come with remote access.

Organizations are now placing additional emphasis on cataloging enterprise data. By prioritizing self-service, organizations are establishing business-ready data catalogs, enabling on-demand data search, access and usage of data from home.

Forward-Thinking Companies Prioritize Business-First Data Catalogs
Last year, the adoption of data governance transformed industries and organizations. Conversely, creating a significant buzz around the data catalog.

A data catalog is a tool used by businesses today to provide access to a plethora of enterprise data. While data catalog tools excel at harvesting and cataloging technical metadata, broader adoption and value decline without clarity into data definitions, synonyms, and how data relates to business processes and outcomes. In 2021, organizations will look to adopt a new kind of data catalog tool that leverages 3D data lineage. With 3D lineage in a data catalog, regardless of the role, individuals can visualize data's origins, route across systems, transformations and impact on business processes and operations. Companies can also automatically add business knowledge around their data catalog, creating broader adoption and strengthening organizational data governance culture.

Boosting Data Literacy by Adding Business Context Around Data
For years, organizations have tried to solve the challenge of connecting data to business context. Leaders bring together teams to work toward the ultimate goal - establishing a common understanding among technical and non-technical users who work with data.

Increasingly, automated data lineage technologies strengthen and facilitate data literacy. Automated data lineage enables companies to provide detailed and precise business context around enterprise data assets and empower business users to trust, understand and benefit from data.

As businesses continue to invest in modern tools and technologies that automate data processes, organizations can provide detailed business context around their data and improve data understanding among business users. In 2021, with 3D lineage and a business-ready data catalog, organizations significantly enhance data trust, deliver ROI and equip the business for today and the future.

The Rise of Data Governance and Quality for DataOps
The need for speed is critical in business. For years, organizations have increasingly leveraged DevOps techniques to accelerate product and service time to market. Heading into 2021, companies are taking a similar approach to data management. Meaning, they are building multi-functional data teams to streamline data pipelines and manage the ever-increasing volumes of data. DataOps processes and platforms facilitate data management and data governance procedures. As a result, organizations deliver high-quality data for business users to quickly analyze and develop insights.

Executing Data Transformation Initiatives with Data Governance First
As more organizations successfully modernize IT infrastructures to reduce cost and increase efficiency, data governance and data quality have shifted. Instead of siloed, often reactive projects, governance and quality together are integral parts of modernization efforts. Merging data governance and quality projects enables organizations to increase the ROI of these initiatives and empowers business users to access high-quality data fit for purpose. Consequently, business users gain trust and confidence in analyzing information for data intelligence.

Massive Shift from Batch Data Processing to Streaming Data
With 2.5 quintillion bytes of data generated every day, we're undergoing a sharp transition away from batch data processing techniques. Last year, companies utilized real-time, streaming data to deliver speed to insights and disrupt the future. Also known as an event-driven architecture, streaming data software, like Apache Kafka, structures information as a stream of distinct changes to the state of data, delivering real-time access to data and insights.

In 2021, organizations will look to address streaming data quality to increase the benefit of streaming data. Businesses will rely on automated tools that ensure the accuracy and reliability of streaming data to increase sales volume, market share and expand profits. By relying on automated tools for streaming data quality, organizations can eliminate manual data quality tasks and keep up with the speed of streaming data.

Building Smarter Data Trust Improves the Customer Experience
Optimizing data as a strategic asset is critical to the customer experience. Improving access to reliable data is why there are significant investments in analytics programs. However, customer data quality is still a real challenge, especially as third-party customer data sharing accelerates. The definition of customer data quality is no longer about address standardization and cleansing routines. Instead, it is about contextual data quality based on customer and third-party data patterns. Advancements in data quality capabilities, machine learning and analytics enable automation of data quality to proactively uncover data quality insights. With automation, organizations no longer rely on defined rules to validate data, allowing them to trust the data they use to deliver a seamless customer experience.

To learn more about Infogix’s 2021 data predictions, visit www.infogix.com or @infogix.

To learn more about 3D data lineage and providing business context around data, visit https://www.infogix.com/infogix-completes-3d-lineage-vision-in-data360-connecting-critical-data-to-business-processes-and-operations/.

About Infogix, Inc.
In our fourth decade as an industry pioneer, Infogix continues to provide large and mid-market companies around the globe with a broad range of integrated and configurable tools to govern, manage and use data. From operations and the office of data to sales, from product and customer service to marketing—users across the entire organization rely on our software to remove barriers to data access, accelerate time to insight, increase operational efficiency and confidently trust business decisions. Our best in class retention rate is proof of our customer-centric focus as we partner with them to thrive in today's data-driven economy. To learn more visit www.infogix.com or @Infogix.
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Issued By Connect Communications
Country United States
Categories Business , Industry , Technology
Tags IT , Data
Last Updated December 8, 2020