5 Common Data Governance Pain Points for Analysts & Data Scientists
<p>Are you an analyst or data scientist at a large organisation?</p>
<p>Raise your hand if you’ve ever come across these head-scratchers:</p>
<ul>
<li><strong>Finding data</strong> felt like going on a <em>Sherlock</em> expedition.</li>
<li><strong>Understanding data lineage</strong> was impossibly frustrating.</li>
<li><strong>Accessing data</strong> became a showdown with the red tape monster.</li>
</ul>
<p>Here’s a common quip I hear from citizen and professional analysts alike:</p>
<blockquote>
<p>“Those data governance guys sure know how to make life interesting…”</p>
</blockquote>
<p>It’s time to cut them some slack.</p>
<p>Drawing from my experience as an engineer and data scientist at one of Australia’s banking giants for <a href="https://towardsdatascience.com/from-data-warehouses-and-lakes-to-data-mesh-a-guide-to-enterprise-data-architecture-e2d93b2466b1" rel="noopener" target="_blank">half a decade</a>, I’ve had the privilege of straddling both sides of this heated fence: being a hungry consumer of data while simultaneously standing as a gatekeeper for others.</p>
<p><a href="https://towardsdatascience.com/5-common-data-governance-pain-points-for-analysts-data-scientists-8efe8a007ac2">Visit Now</a></p>