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8 data strategy mistakes to avoid

CIO Business Intelligence

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. Overlooking these data resources is a big mistake. What are the goals for leveraging unstructured data?”

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Who Needs Big Data Analytics Software?

Jet Global

Of all the transformative effects the internet has had on the world of business, none is more dramatic than the proliferation of data it has enabled. Over the past few years, we’ve already seen transformation on a massive scale thanks to how businesses are harnessing and utilizing the new wealth of data available to them.

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Who Needs Big Data Analytics Software?

Jet Global

Of all the transformative effects the internet has had on the world of business, none is more dramatic than the proliferation of data it has enabled. Over the past few years, we’ve already seen transformation on a massive scale thanks to how businesses are harnessing and utilizing the new wealth of data available to them.

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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

Type of Data: structured and unstructured from different sources of data Purpose: Cost-efficient big data storage Users: Engineers and scientists Tasks: storing data as well as big data analytics, such as real-time analytics and deep learning Sizes: Store data which might be utilized.

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11 dark secrets of data management

CIO Business Intelligence

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

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Get Ready For These Six 2020 Business Intelligence Trends

Smart Data Collective

New Avenues of Data Discovery. New data-collection technologies , like internet of things (IoT) devices, are providing businesses with vast banks of minute-to-minute data unlike anything collected before. NLP may also improve data collection by enabling AI to scan through and organize text-heavy, unstructured data.

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

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