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During its digital Ataccama Innovate 2021 event, Ataccama today announced general availability of the next major upgrade to its data management platform, which relies on an expert system and machine learning algorithms to automate processes.
The company also released the results of a global survey of more than 1,000 executives and business users — from midsize to large enterprises. The survey finds 79% of executives and 75% of line-of-business users are contending with data quality issues at a time when more than three-quarters of respondents (78%) are collecting and processing more data now than they were prior to the pandemic.
Conducted by ResearchScape, the survey also finds over half of users (55%) require additional help to transform data to fit their purpose, with 44% having to wait a day or more to get help from a technical user or IT team.
The top three impacts of poor data quality identified by respondents are slower times to data insight (46%), negative impacts to business performance and decision-making (42%), and negative impacts on strategic initiatives (40%). But close to half of survey respondents (43%) admit they have implemented data governance strategies at either a low maturity level or not at all.
Specifically, survey respondents are looking to implement processes to better organize data (59%), consolidate documented data (55%), and ensure data is only used for purposes that are compliant with regulations (40%).
The survey results suggest executives are now a lot more conscious of the need to consistently manage data as they invest in AI-enabled digital business transformation initiatives that require access to massive amounts of data, Ataccama CEO Michal Klaus said.
In fact, the top priority technologies survey respondents identified for the next 12 months are AI or machine learning (43%), data governance (41%), data security (41%), and data quality management (37%).
The Ataccama ONE Gen2 platform is an expert system that has been optimized to manage large volumes of disparate data, Klaus said. It enables organizations to create data profiles, track data quality monitoring, set up data previews to better understand the relationship between different datasets, and enforce the policies that determine which end users are allowed to access what data. Earlier this year, Ataccama acquired Tellstory to add data visualization capabilities to the data catalog that has been revamped as part of the latest release of its platform.
Tasks and processes that are being enhanced using AI capabilities include data classification, rules suggestion, relationship and data lineage discovery, anomaly detection, pattern matching, data quality monitoring, and integration with master data management (MDM) tools Ataccama provides.
As organizations invest more in data lakes and data warehouses, they are discovering the limitation of their existing data management processes. In many cases, the return on investment in those data lakes never materializes because there’s no way to navigate all the data being dumped into them, Klaus notes, adding “They become data swamps.”
Ultimately, the goal is to provide a data management platform that makes it simpler for IT teams to enable end users to self-service their own data needs at scale in a way that complies with privacy regulations and other considerations, Klaus said.
Most IT organizations are not especially proficient when it comes to data management, and data is typically managed within the context of the application employed to create it. This means applications wind up creating data that is often conflicting because, for example, the way a customer is described varies from one application to the next. Applying advanced analytics to data depends on IT teams addressing data quality issues that stem from the way different application silos have rendered data. It not uncommon for much of that data to also be incomplete or simply wrong.
Regardless of the tools employed to clean up that mess, data management will need to become a lot more automated than it is today to address the true scale of the challenges ahead.
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