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June 2020 Newsletter
Prioritizing Business-Critical Data Initiatives and our Collibra Excellence Award
One approach we’ve taken is to help clients standardize a key process within the data supply chain – data acquisition. As this can be a complex, inefficient and costly process, we’re already seeing small wins with implementing a standardized framework.
ICYMI, we previously shared key insights and best practices on tackling inherent data acquisition challenges. Next month on the blog, we’ll dive into the specifics of an optimized data acquisition framework and how to leverage Collibra to manage and govern it.
Speaking of Collibra, we were thrilled to receive Honorable Mention as Collibra Partner of the Year, announced earlier this month at their Data Citizens digital event. The nomination was in recognition of our efforts to proactively support mutual clients who have struggled to gain traction. To further accelerate this technology adoption journey, we created Nine Best Practices for Driving [Enterprise] Collibra Adoption, our latest in-depth Guide.
The goal? Optimized value of Collibra adopted across the organization and integrated into core project, analytic and operational processes.
Complimentary Guide: Nine Best Practices for Driving [Enterprise] Collibra Adoption
If your organization has invested in Collibra to enable data governance and metadata management, you’re one step closer to expediting speed to insight and making data intelligence meaningful.
The value of Collibra is optimized when its use is embedded into people’s daily work and the processes and procedures they rely on, essentially becoming “business as usual.” This creates a sustainable need as opposed to just knowing it is one of many tools available.
In Nine Best Practices for Driving Enterprise Collibra Adoption,
we provide in-depth best practice tips and vetted approaches for critical ways to accelerate adoption.
The featured nine best practices are:
1. Focus on the value use case
2. Engage the right people at the right time
3. Align technology adoption with change management
4. Communicate early and often
5. Make training meaningful and accessible
6. Measure impact and progress
7. Plan for and manage resistance
8. Integrate (meta)governance
9. Blend agile and traditional approaches to data governance
Quantify the Value (and Meaning) of Data
Data is the lifeblood of our digital economy, with significant resources spent on enabling information management and analytic capabilities. Yet less than 10 percent of CDOs measure the financial value of their data and analytics programs.
In Quantify the Value and Meaning of Data, Kelle O’Neal shares her insights for a thoughtful strategy and effective framework for defining data assets and understanding why measuring data as an asset matters.
Next-Generation Data Governance Learning Plan
Looking for self-paced, on-demand and comprehensive online training for modern data governance?
We partnered with DATAVERSITY to create the Next-Generation Data Governance Learning Plan to build on the information and techniques of foundational governance. The Next-Generation series of seven courses will:
- Review how organizations and operating models have evolved to address greater demands for agility, output and new trends in technology
- Examine the role of metadata management and data governance in data privacy, data ethics, data definitions, business glossaries and data catalogs
- Dive deep into organizational change management to ensure adoption and value
When you purchase this course, don’t forget to enter code FSFP at checkout to save 20%.