Remove Data Collection Remove Data Quality Remove Machine Learning Remove Unstructured Data
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What Tools Do You Need To Manage Unstructured Data?

Smart Data Collective

Unstructured data represents one of today’s most significant business challenges. Unlike defined data – the sort of information you’d find in spreadsheets or clearly broken down survey responses – unstructured data may be textual, video, or audio, and its production is on the rise. Centralizing Information.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science.

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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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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Analytics 131
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The 10 most in-demand IT jobs in finance

CIO Business Intelligence

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Business analyst.

Finance 98
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The 10 most in-demand IT jobs in finance

CIO Business Intelligence

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Business analyst.

Finance 98
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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. An even larger issue is that people may not know how to see value in data.