Key Takeaways

• “With the rise of digital transformation and the need to create a digital workforce, employees' data literacy has become an increasingly important part of an organization's overall digital dexterity.”

• There are three approaches that CDOs can follow to measure the efficacy of their data literacy initiatives:

  - Measure the Success of a Data Literacy Program Rollout. “Set employee engagement and satisfaction scores to demonstrate the success of the data literacy program.”

  - Evaluate the Successful Progress of Employees With Data Literacy Improvement. “To validate that employees gained the intended knowledge, skills, attitude, confidence, and commitment, use progress assessments and performance criteria.”

  - Measure Data-Driven Business Outcomes. “Demonstrate a clear link between business outcomes and data literacy training to communicate its success.”

• “To achieve better business outcomes, organizations must have a data-literate culture that values information as an asset.”

Key Takeaways

• “Top trends in D&A technology and practices create new sources of value by helping organizations anticipate change and transform extreme uncertainty into new opportunities.”

• The top 10 trends for D&A in 2023 are:

1. Value Optimization 

2. Managing Your Artificial Intelligence (AI) Risk

3. Data Sharing is Essential 

4. D&A Sustainability 

5. Observability 

6. Practical Data Fabric

7. Emergent AI

8. Converged and Composable Ecosystem

9. Consumers Become Creators

10. Humans Remain The Decision Makers 

• “Data observability is the ability of an organization to have a broad visibility of its data landscape and multilayer data dependencies at all times with an objective to identify, control, prevent, escalate and remediate data outages rapidly within expectable SLAs.”

• “D&A and artificial intelligence (AI) are increasingly being used by organizations to monitor and benchmark environment, social and governance (ESG) goals and, more importantly, to improve sustainability.”

• “Emergent AI enables organizations to apply AI in situations where it is not feasible today, making AI ever more pervasive and valuable.”

• “Not every decision can or should be automated. Efforts to drive decision automation without considering the human role in decisions will result in a data-driven organization without conscience or consistent purpose.”

  Learn more from the Gartner Top Trends in D&A in the associated Gartner press release: Gartner Identifies the Top 10 Data and Analytics Trends for 2023.
  

Key Takeaways

• “Migrating the D&A platform to the cloud requires evaluating each component and workload separately to determine the suitability, compliance obligations, benefits of cost optimizations and price-for-performance constraints in moving to the cloud.”

• “Organizations evaluating cloud strategies for data and analytics applications must first identify whether to deploy their new system on-premises using the private cloud, have a single public cloud service provider or use multiple public cloud service providers.”

• “The success of D&A architecture requires an ecosystem that is easy to use.”

• “Re-architect the D&A components when migrating to cloud instead of lift & shift.”

• A pipeline-like approach is best when deploying your D&A architecture.” 

• “Invest in the upskilling of your team. Organizations must leverage top-down and bottom-up approaches for upskilling and bring in consultants with expertise in areas where there are gaps.”