Data Canvas: Most Brands Are Planning Tech Investments Despite Hurdles

Almost all companies are planning data initiatives for 2023. But it won’t be easy for them, judging by a new study from Tamr, Inc.  

Of the companies polled, 93% have big data plans. For instance, 75% are focusing on improving data quality and 65% on investing in data management technologies.  

But over 50% admit they face obstacles in achieving all this, some of which could hurt their ability to send data-based emails in a timely way. 

For instance, 46% are still cleaning their data using manual processes. And 70% feel their company needs help turning data into valuable business insights, while almost 60% has trouble realizing business value from its use of data.

Tamr argues that firms are hampered by legacy tools such as rules-based master data management (MDM), traditional data warehouses and data lakes.

“From data culture and modern data mastering to consumption-based data governance and streaming/Kafka-like architectures, organizations must embrace change to deliver clean, curated, continuously updated data products assembled from thousands of source systems to all potential data consumers in their enterprise," says Andy Palmer, co-founder, chairman and CEO of Tamr.  



Palmer adds. "Although we've seen companies make significant strides over the past decade, our research shows that many organizations still have a long road ahead.

On the positive side, 95% expect their firms to make more significant investments in AI and machine-learning technologies. But this requires a change in their data cultures. 

CIOs have for 40 years struggled use data as a strategic weapon. But chief data officers (CDOs) are now emerging to take responsibility for data. 

Of the marketers polled, 60% feel the CDO role needs to expand beyond overall data stewardship to become more data-centric. And roughly 55% feel data scientists must be integrated into the rest of the business.

On another front, over 95% agree that data security and privacy will become more critical as the volume and complexity of data increases. 

For its part, Tamr argues that the best no-code AI tools: 

  • Integrate easily
  • Accelerate processes 
  • Cost less than custom AI. 
  • Empower business intelligence at scale. 
  • Enable brands to realize quick time to value.

Tamr surveyed 500 data leaders. 



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