Don Quixote Lives: Another Assault on Data Silos
June 3, 2021
Keep in mind that in some organizations data silos are necessary: Poaching colleagues (hello, big pharma), government security requirements (yep, the top Beltway bandits too), and common sense (lawyers heading to trial with a judge who has a certain reputation). Data silos are like everywhere. The were a couple of firms which billed themselves as “silo breakers.” How is that working out? The answer to the question resides in an analyst’s “data silo.” There you go.
Security is the biggest reason much-maligned data silos, also known as fragmented data, persist. Google now hopes to change that, we learn from “Google Cloud Launches New Services for a Unified Data Platform” at IT Brief. The company asserts its new solutions mean organizations can now forget about data silos and securely analyze their data in the cloud. We have yet to see detailed evidence for that claim, however. We will continue to keep our sensitive data separated, thank you very much.
Writer Ryan Morris-Reade describes the three new services upon which Google is pinning its cloudy unification hopes:
- Datastream, a new serverless Change Data Capture and replication service. Datastream enables customers to replicate data streams in real-time, from Oracle and MySQL databases to Google Cloud services such as BigQuery, Cloud SQL, Google Cloud Storage, and Cloud Spanner. This solution allows businesses to power real-time analytics, database replication, and event-driven architectures.
- Analytics Hub, a new capability that allows companies to create, curate, and manage analytics exchanges securely and in real-time. With Analytics Hub, customers can share data and insights, including dynamic dashboards and machine learning models securely inside and outside their organization.
- Dataplex, an intelligent data fabric that provides an integrated analytics experience, bringing the best of Google Cloud and open-source together, to enable users to rapidly curate, secure, integrate, and analyze their data at scale. Automated data quality allows data scientists and analysts to address data consistency across the tools of their choice, to unify and manage data without data movement or duplication. With built-in data intelligence using Google’s best-in-class AI and Machine Learning capabilities, organizations spend less time with infrastructure complexities and more time using data to deliver business outcomes.”
We learn consulting firm Deloitte is helping Google implement these solutions. That company’s global chief commercial officer emphasizes the tools provide “enhanced data experiences” for companies with siloed data by simplifying implementation and management. We are also told that Equifax and Deutsche Bank trust Google Cloud with their data. I guess that is supposed to mean we should, too.
But Google is quite the fan of data silos. Remember “universal search.” Google has separate indexes for news, scholarly information, and other content types. Universal implies breaking down “data silos.” But it is easier to talk about solving the data silo problem than delivering.
And what about Deloitte? This firm was fined about $20 million US because it had data silos which partitioned some partners from the work of the professionals working for Autonomy.
Yep, data silos. Persistent and embarrassing when someone thinks of “universal search” and Deloitte’s internal oversight methods.
Cynthia Murrell, June 03, 2021
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