Remove Data Quality Remove Software Remove Unstructured Data
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The state of data quality in 2020

O'Reilly on Data

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

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8 tips for unleashing the power of unstructured data

CIO Business Intelligence

With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides. Unstructured data resources can be extremely valuable for gaining business insights and solving problems.

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5 tips for better business value from gen AI

CIO Business Intelligence

Abhi Maheshwari, CEO of AI software vendor Aisera, says, Gen AI provides many benefits for sales, and key metrics for assessing its impact include conversion rate, sales cycle length, average deal size, win rate, and lead volume. In HR, measure time-to-hire and candidate quality to ensure AI-driven recruitment aligns with business goals.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. From automating tedious tasks to unlocking insights from unstructured data, the potential seems limitless. You get the picture.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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The DataOps Vendor Landscape, 2021

DataKitchen

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

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Handling real-time data operations in the enterprise

O'Reilly on Data

For big data, this isn't just making sure cluster processes are running. A DataOps team needs to do that and keep an eye on the data. With big data, we're often dealing with unstructured data or data coming from unreliable sources. Shouldn't the data engineering team be responsible for this?