Data has been the driving force of the decade. Digital pioneers like Amazon, Netflix and Uber account for some of the most extreme market disruption their respective industries have faced.
But such success cannot be attributed soley to head-starts.
Many organizations have tried and failed to become truly “data-driven,” and many organizations will continue to do so.
The difference between success and failure is often a deeper understanding of the data behind an organization’s operational decisions.
With a deeper understanding of their data assets, organizations can realize more trustworthy and effective analysis.
Such understanding also equips organizations to meet customer demands as well as deal more effectively with the regulatory landscape – which is evolving at a fast rate.
To help you prepare for 2020, we’ve compiled some of the most popular data governance and metadata management blog posts from the erwin Experts from this year.
A strong data governance framework is central to the success of any data-driven organization because it ensures this valuable asset is properly maintained, protected and maximized.
But despite this fact, enterprises often face push back when implementing a new data governance initiative or trying to improve an existing one:
Data scientists and other data professionals can spend up to 80 percent of their time bogged down trying to understand source data or address errors and inconsistencies.
That’s time needed and better used for data analysis.
In this metadata management blog, the erwin Experts assess four use cases that demonstrate exactly how metadata-driven automation increases productivity:
Data mapping tools help organizations discover important insights.
They provide context to what otherwise would be isolated units of meaningless data.
Now with the General Data Protection Regulation (GDPR) in effect, data mapping has become even more significant:
Businesses stand to gain a lot from unifying their data platforms.
Data-driven leaders dominate their respective markets and inspire other organizations across the board to use data to fuel their businesses.
It was even dubbed “the new oil at one point” but data is arguably far more valuable than that analogy suggests:
The California Consumer Privacy Act (CCPA) and GDPR share many of the same data privacy and security requirements.
While the CCPA has been signed into law, organizations have until Jan. 1, 2020, to enact its mandates. Luckily, many organizations have already laid the regulatory groundwork for it because of their efforts to comply with GDPR.
However, there are some key differences, which the erwin Experts explore in a Q&A format:
Digital transformation involves synthesizing an organization’s people, processes and technologies, so involving business architecture and process modeling is a best practice organizations can’t ignore.
The following post outlines how business architecture and process modeling work in tandem to facilitate efficient and successful digital transformation efforts:
Having a clearly defined digital transformation strategy is an essential best practice to ensure success.
But what makes a digital transformation strategy viable? Learn here: