Ohalo, a software provider for enterprise-wide unstructured data discovery, classification and compliance management, strategically partners with Collibra, a Data Governance company.
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Data breach can cost you everything. In the US alone, 4.1 billion records were exposed due to data breaches in the first six months of 2019. Alarming!
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When managing private and sensitive data, dealing with unstructured data can be challenging. For the most part, this is because of the sheer amount of it a company can generate.
For one, we've mentioned that the average employee creates on average over 1,000 files during their tenure — and so companies handling 10,000 employees will have to handle tens of millions of files in as little as one year. When you add data privacy and security concerns, this task is made even harder.
Conversations about unstructured data in the mainstream have only popped up in the past 2 or 3 years. Yet it has and will continue to be instrumental in your day-to-day operations, so it's crucial to know exactly what it is, where it is and why it's so important today.
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Around 80% of a company’s data is unstructured dark data. Although to date much focus has been on structured data because it is easier to get a grasp of, unstructured data proliferates with the daily activities of staff, from the important aspects of how deals get done to the more mundane scheduling of after work drinks.
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Many companies are looking to modernise and migrate their on-premise data to the Cloud. Often it’s shifting legacy applications, looking to take advantage of new database types and cloud-based data platforms, bolstering cybersecurity, and driving analytics and insights. With the average employee creating 1,000 files during their tenure at a company and little control over how that data is stored, unstructured data is hugely challenging to deal with during data migration projects to the Cloud.
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Bringing better safety outcomes to the construction industry to get workers home safely to their families
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Bringing better safety outcomes to the construction industry to get workers home safely to their families
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Last week Apple confirmed that applications may be banned from the App Store if they don't meet Apple's new App Tracking Transparency feature. Is this the first major sign of privacy emerging as a core market value?
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A few thoughts on the increasing popularity of wearable tracking technologies that a number of organisations are now using in their pandemic response to measure and halt transmission. These would seem to open up major personal data liabilities under data privacy legislation.
Is data minimisation the correct response?
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Machine learning and NLP has really taken off in the enterprise over the past couple of years. Our Data X-Ray product heavily rely on the advances in machine learning to deliver everything from privacy preserving data science pipelines for safety reports to identifying documents for data retention project implementations.
What are others seeing out there in enterprise applications of NLP?
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