We’ve all heard the war stories born out of wrong data: These stories don’t just make you and your company look like fools, they also cause great economic damages. And the more your enterprise relies on data, the greater the potential for harm. Here, we take a look at what data quality is and how the entire data quality management process can be improved.
Cloudera services logs offer a breadth of information to assist in cluster maintenance; from assisting in security checks, auditing tasks, and validation for performance tuning and testing tasks – to name a few. However, log records generated by these services do not hold the same value for every organisation.
The customer has never been more right. Across industries, customers have become conditioned to demand not only near-instant responses to their needs but that their needs be anticipated in advance. Financial institutions are not given a pass, despite a competitive landscape flooded with regulation and privacy considerations. The customer still has expectations for a personalized, timely, and relevant experience.
The push to embrace cloud-based technologies has undoubtedly transformed IT infrastructures at every level of government. Federal, state, and local agencies have made significant strides in modernizing how data is collected, stored, and analyzed, all in service of their mission and in fulfillment of strategic IT mandates.
At Cloudera Fast Forward we work to make the recently possible useful. Our goal is to take the incredible data science and machine learning research developments we see emerging from academia and large industrial labs, and bridge the gap to products and processes that are useful to practitioners working across industries.
Broadcasting is now available in this release for both dashboards and presentations. Just like reports, you can now enable scheduled delivery of these analytic content to different audiences. We have also included additional options for schedules — making it more granular for specific frequencies. For example, for fortnightly broadcasts I can now set the delivery to be on the second Monday. Or for monthly broadcasts, to have deliveries happen on the fifth day every month.
The infamous data science workflow with interconnected circles of data acquisition, wrangling, analysis, and reporting understates the multi-connectivity and non-linearity of these components. The same is true for machine learning and deep learning workflows. I understand the need for oversimplification is expedient in presentations and executive summaries. However, it may paint unrealistic pictures, hide the intricacies of ML development and conceal the realities of the mess.
