Data quandary: How data quality and timeliness issues have increased in the past three years

by | May 26, 2022 | Public Relations

For decades, the data warehouse was the standard for archiving and retrieving data for analysis and reporting. However, the emergence of new data architectures, coupled with the exponential growth in the volume and velocity of data organizations can analyze, have created new challenges and opportunities for IT teams. To search, access, and leverage the insights these new data sources offer, enterprises need to modernize the way they design, implement, and manage their data delivery and analytics systems.

New research from data lake activation firm ChaosSearch analyzes how organizations are leveraging modern data architectures, such as data warehouses, data lakes, data lakehouses, data mesh, and data fabric. The survey was conducted by Unisphere Research, and fielded among the subscribers of Database Trends and Applications (DBTA).

Data quandary: How data quality and timeliness issues have increased in the past three years

“The heavy reliance on older data infrastructures and warehouses is hindering organizations’ ability to become data-driven,” said Joe McKendrick, research analyst and author of the 2022 Data Delivery and Consumption Patterns Survey, in a news release. “This survey highlights the need for more modern, cloud-based solutions that expedite and democratize data analysis across the enterprisewithout compromising data quality. It would be wise for every IT and data professional to consider how much time they spend organizing, transforming, and prepping data to be analyzedand to consider how a new solution might solve for those headaches.”

The 2022 Data Delivery and Consumption Patterns Survey examines these trends in more detail to determine current data environments, purchasing plans for 2022 and beyond, and perspective from those working to build and leverage data environments.

Data quandary: How data quality and timeliness issues have increased in the past three years

Data warehouses are still foundational data architecture—though teams have started exploring new solutions

Data warehouses are used at 82 percent of the enterprises surveyed. Meanwhile, about half of enterprises have implemented data lakes, and one in five have adopted data lakehouses, as well as considering the role of data mesh and/or fabric, to support decision making.

Investments in data lakes, specifically, are on the rise

More than half of data executives (56 percent) indicate they will be ramping up their spending on data lakes over the next three years. Data lake users specifically are well-invested in their infrastructures, with 66 percent of this group planning for growth.

Data quality and timeliness are the most pressing issues cited by respondents.

Sixty-five percent report these issues have increased over the past three years, with 20 percent of the increase reported as “substantial.” Additionally, 69 percent of respondents using data warehouses say their data delivery issues have increased.

There’s still latency and lag time for many organizations when it comes to delivering data to users within the enterprise

Forty-four percent say it takes a day or longer for users to get the data they need. A majority of traditional data warehouse users (51 percent) report such a lag.

Data replication has increased over the last three years

This is according to 71 percent of respondents. Twenty-three percent report this increase as “significant”which is likely causing greater issues tied to cost, complexity, and data access.

Data lakes and data lakehouses support a widely diverse set of workloads

Not only do data lakes support analytics and decision support (cited by 98 percent of respondents), but they also support customer transactions, artificial intelligence/machine learning, and big data clustersaccording to respondents.

Data quandary: How data quality and timeliness issues have increased in the past three years

“The need to store and access data has been critical to enterprise success for decades, but it has never been possible for companies to search and analyze that data from within the same architecture,” said Thomas Hazel, CTO, Founder, and Chief Scientist at ChaosSearch, in the release. “With the emergence of new, cloud-based, modern data platforms, organizations now have the power to accelerate their analytics initiatives and overcome the barriers created by traditional databases—such as manual data prep and transformation. This survey highlights the growing need amongst data professionals to deliver unified search and SQL analytics that power better business decisions, which is the exact opportunity our data lake platform aims to create.”

Data quandary: How data quality and timeliness issues have increased in the past three years

Download the full report here.

The survey was conducted by Unisphere Research, a division of Information Today, Inc., in partnership with ChaosSearch. More than 200 IT leaders and professionals among the subscribers of DBTA were surveyed. The most common job titles among survey respondents were directors/managers of IT, directors/managers of analytics, and data architect. Popular industries included technology, financial services, healthcare, manufacturing, and telecommunications. Two out of five survey respondents were from companies with 5,000 or more employees.

Richard Carufel
Richard Carufel is editor of Bulldog Reporter and the Daily ’Dog, one of the web’s leading sources of PR and marketing communications news and opinions. He has been reporting on the PR and communications industry for over 17 years, and has interviewed hundreds of journalists and PR industry leaders. Reach him at richard.carufel@bulldogreporter.com; @BulldogReporter


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