FirstEigen

[FirstEigen @FirstEigen]

Compare and reconcile data in different #AWS #S3 buckets automatically with AI Agents. If you are updating your #ETL or switching to a new ETL vendor, you should verify that the new ETL performs exactly what the old ETL did. https://t.co/vYrXhHWiDf via @YouTube

[FirstEigen @FirstEigen]

Check out my latest article: Data Preprocessing with AI Guardrails to Reduce Anti-Money Laundering (AML) False Alerts by 50% https://t.co/RtGuK63ade via @LinkedIn

[Sandeep Shouche @SandeepShouche]

Staff, EC members and family gathered today at @sevavardhini to assemble the first lot of Diwali kits to be sent to our sisters. Please use the information provided to send in your contribution or share with others if you can. Thank you for your support.

[FirstEigen @FirstEigen]

Check out my latest article: How to Architect Data Quality on Snowflake – Serverless, Autonomous, In-Situ Data Validation https://t.co/VOz1Au3i6l via @LinkedIn

[FirstEigen @FirstEigen]

Data errors due to “Systems Risks” are the biggest contributors to untrustworthy data. As ETL jobs move data between systems, errors creep in and steadily multiply like cancer across an enterprise. @FirstEigen https://t.co/kRvWd96JzQ #DataValidation #DataQuality #DataErrors

[FirstEigen @FirstEigen]

How inaccurate data damages brands... Brands take years to build. An error or two can destroy it in an instance. @FirstEigen @DataBuck https://t.co/nqUSb7GkMV #DataValidation #DataQuality #DataErrors

[FirstEigen @FirstEigen]

Why is autonomous #dataquality validation important? https://t.co/AqIvDQTTN9 @FirstEigen #Datavalidation #dataquality #dataerrors

[FirstEigen @FirstEigen]

Intro to Databuck, autonomous cloud data quality monitoring & val... https://t.co/QQQ6GKRQaJ via @YouTube

[FirstEigen @FirstEigen]

@Citibank Trial is a wake up call for #Banks to autonomously monitor and validate data https://t.co/s7VmMexZQy via @YahooFinance

[FirstEigen @FirstEigen]

DataBuck Monitor- setup data monitoring on AWS https://t.co/ezw6ic5wWZ via @YouTube
Monitor #Cloud data on #AWS with DataBuck Monitor. Know the health of your data assets, its #DataQuality and track its ups and downs autonomously with #AI/#ML.

[Larry Kim @larrykim]

🤔Stop apologizing, start thanking

[FirstEigen @FirstEigen]

Smart #DataQuality Tip-18: Virus pandemic causes distress because its impact is measured. #DataQuality pandemic spreads like a virus, is pernicious and is seldom quantified. DataBuck Autonomous DQ monitoring stops poor data pandemic infecting your systems.

[FirstEigen @FirstEigen]

When #DataQuality is ignored by companies before printing #W2 forms for their employees they pay a huge price. FirstEigen can validate such data automatically w/o human inputs. https://t.co/XeXH5567ma

[FirstEigen @FirstEigen]

Validate #Cloud #DataQuality without human intervention. #DataQuality rules are auto discovered, auto executed and auto updated over time. For Amazon Web Services (AWS) and @Snowflake Computing Cloud you can try it right now. https://t.co/nAzWxKSQcu

[FirstEigen @FirstEigen]

"Run out of chocolate, and that’s a shame. Run out of oxygen and you’re doomed" by @SethGodin. A lot of software buyers can't distinguish between the two. Start with what job is important to you now (oxygen), then boil the ocean fo…https://t.co/4UyZDsjQG0 https://t.co/ZX12S9d0pU

[FirstEigen @FirstEigen]

Back office of 80% of @Accenture clients deeply lag their front office. The front office wants data-driven decisions, but the back-office has inaccurate insights due to poor #DataQuality. Adopt autonomous DQ Soln w/ @FirstEigen https://t.co/0qX6Kdt16l

[FirstEigen @FirstEigen]

Smart #DataQuality Tip-3: Static #DataValidation rules for the Cloud are error prone and not scalable. Best firms validate data accuracy based on their firm-specific historical business context with dynamic checks, & not generic, static checks

[FirstEigen @FirstEigen]

From over 80 data-intensive projects across several industries, @@GKrasadakis notes, #DataQuality is critical in the era of automated decisions. The non-obvious challenge that derailed projects was poor data issues, which in most c…https://t.co/fzxRzv8BBp https://t.co/URiZQr1gRz

[FirstEigen @FirstEigen]

Smart #DataQuality Tip-5: Traditional old method of DQ = Profiling + Fixed Rules + Coding. Unexpected data errors sneak & increase existential risk. #CognitiveDataQuality = Auto rules discovery + Auto rules update. Reduces #DataGovernance risk by 10x

[FirstEigen @FirstEigen]

Smart #DataQuality Tip-7: Michael Jordan can swim but he can’t be Michael Phelps in the pool. #Governance or #Profiling or #DataPrep software won’t decrease your nightmare from bad data. Hire the right software for your specific #DataQuality need