Tatiana Ladygina
Tatiana Ladygina
Senior Manager, Product Marketing
November 22, 2022

Four Takeaways from Women Data Leaders Summit

Four Takeaways from Women Data Leaders Summit

Earlier this month, I had the pleasure of attending the 2nd annual Women Data Leaders Global (WDL) Summit hosted by CDO Magazine and the EDM Council. The WDL Summit brought together seasoned female data leaders to discuss data-driven business transformation. Speakers and attendees shared thoughts and experiences on how to build and execute a modern data architecture, how to navigate numerous data challenges (e.g., quality, variability and availability), and how to do so in alignment with strategic business initiatives. Here are a few highlights from the Summit.

1. Diversity is key to success

By now, we should all be well aware of the critical role diversity plays in the workplace. Diversity in terms of age, gender, nationality, education, professional background and experience, ways of thinking, and leadership styles, to name a few, leads to a more innovative, transparent, and less-biased environment. As important, workplace diversity also ensures data diversity, which is critical in data-driven decision making. According to McKinsey, organizations with more diverse teams are 48% more likely to show excellent business performance than those with less representation. Why? Dianne DeRoze, Sr. Manager at AWS Training and Certification and one of the WDL speakers, alluded to an HBR article that states that diverse groups are 54% more likely to make the right business decision. Although much has been done in recent years to increase awareness of this topic, there is still room for improvement for the data industry to drive positive change.

2. Recipe for a solid data architecture

Organizations across industries have embarked on the challenging but critical journey of building a modern data architecture. Given the fluidity of the business environment and the unprecedented pace of technological advancements, it is indeed a journey and not a destination. Building a data architecture has many components, ranging from the right people and technology to compliance. An organization’s unique circumstances and goals call for unique approaches to data architecture. Kirsten Dalboe, CDO at Federal Energy Regulatory Commission, shared an excellent cooking analogy to highlight three simple steps that can be applied universally:

  1. When “cooking” your data architecture, start with the right “ingredients” by conducting an inventory of your data assets.
  2. Then, think if you have the right “kitchen appliances” (solutions, applications, platforms) to cook something with your “ingredients.”
  3. Lastly, map out the tech support pieces and build the architecture that is robust yet flexible so you can adjust in a timely manner to a rapidly changing environment.

3. Data culture as the foundation of data quality

Too often, companies seeking an approach to data management fall into the trap of having a dedicated team of “data people” responsible for all the company’s data initiatives. This is a critical mistake. Even though this idea may be true in some cases, it is not universally correct. To succeed in their data management initiatives, organizations must evangelize that all employees are “data people,” regardless of their individual job descriptions. We all consume data in some form or shape. We all add or extract it from internal and external systems and data sources. And more important, we should rely on it to make the right decisions. With a strong and healthy data culture, organizations can continuously improve data literacy and empower people to be more intentional about data throughout its lifecycle. Clean, curated, analytics-ready data sets lead to confident and timely actions and result in strong business outcomes. Democratizing data as a shared asset must be purposeful, actionable, and strategic.

4. The value of a data-driven business

Dirty, junky data holds organizations back from transforming the business from merely existing to thriving. IBM estimated that bad data costs the US $3.1 trillion per year. Hence, it is necessary to transform data into valuable information that fuels insight-driven decision making. In today’s day and age, relying on gut feeling is not enough to run a successful business. Even though the value of experience and the ability to make bold decisions never go out of fashion, modern problems call for modern solutions. Reliable data architecture and trusted data allow business leaders to shape business strategy by supplementing their years of experience and knowledge with invaluable input based on predictions and historical analysis. No matter where you are in your business journey, data quality and reliability are at the core of success. Watch Tamr’s demo and explore our customer stories to learn more about Tamr Mastering, our innovative data mastering solution that helps leading organizations around the world solve their toughest data challenges.