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John Smith
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Data Scientist, USA
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Cloud-Ready Data
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Data Governance

Top 4 takeaways from the Gartner Data and Analytics Conference

Last week I attended the virtual Gartner Data and Analytics Summit. This conference brought together data and analytics leaders from top industries such as government, banking, financial services, insurance, and manufacturing. I attended the keynote address, “Learn, Unlearn, Relearn: The Key to D&A success,” as well as many other sessions focused on governance, data and analytics, the role of the CDO, metadata management and data lakes. Below are my top 4 takeaways from the conference: 

1.  Adaptation

Gartner emphasized and reiterated the concept of adaptation in a number of presentations. By adaptation, Gartner means having technologies and practices that easily, or even automatically, shift to meet the changing needs of the business and market. Organizations can embrace adaptation from a technological perspective through setting up their operating model or adopt adaptive governance strategies for decision-making. Being adaptive allows organizations to remain flexible and make sure all pieces of their data intelligence program and platforms are designed in a way that works for their unique needs. 

2. Organizations must work backwards from business outcomes

Gartner sees data and analytics as a business enabler; it should be consumable to all employees and tied to the business strategy and outcomes. Nonetheless, Gartner asserts that many organizations struggle to drive business value out of their data and analytics programs because there is a gap between the desired outcomes and the steps it takes to achieve data-driven results. When striving to achieve data intelligence, don’t start from the data. Start from the desired business outcomes. Ask yourself and your team, “what are the CEO’s goals? What does she care about? What outcomes does she want to see come to fruition?” Then work backwards to determine  what steps need to be taken to achieve these outcomes. Working backwards will help you identify the fractures between the strategic business outcomes, data and analytics practices, and technology available to you. 

3. Immaturity

Throughout the conference, Gartner mentioned that many organizations may not be as mature in their data and analytics programs as they think they are. Gartner asserts that although organizations are starting to understand the value of data and analytics, their technology, architecture, and employees have not developed enough as whole enough to unlock this value. To reach the level of desired maturity, organizations must conduct an assessment of their current practices, which will  require organizations to assess their talent’s data literacy, rethink their data and analytics vision, and identify new KPIs.

4. Learn, unlearn, relearn 

The current business environment is ever changing. In order to succeed, organizations must be agile and adaptive. Leaders must align to the priorities of the CDO and and the business objectives of the entire company. This requires taking a step back, learning, unlearning, and relearning many concepts. So how does an organization do this? First you need to identify the people and departments who want to change. Work with this team to understand their desired business outcomes and work together to efficiently achieve these goals. Next, look to invest in technologies that can adapt over time. Finally, work to expand your influence by embedding data and analytics into all decisions. Together these steps will help transform your business model and ensure business efficiency.

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