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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes. Their role extends to managing information for corporate decision-making, improving reporting systems , and performing complex analyses. JPMorgan Chase & Co.:

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Unlock The Power of Your Data With These 19 Big Data & Data Analytics Books

datapine

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. If we had to pick one book for an absolute newbie to the field of Data Science to read, it would be this one.

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How Big Data Analytics & AI Combined can Boost Performance Immensely

Smart Data Collective

Let’s not forget that big data and AI can also automate about 80% of the physical work required from human beings, 70% of the data processing, and more than 60% of the data collection tasks. From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g.,

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What is a Data Pipeline?

Jet Global

Data ingestion methods can include batch ingestion (collecting data at scheduled intervals) or real-time streaming data ingestion (collecting data continuously as it is generated). Technologies used for data ingestion include data connectors, ingestion frameworks, or data collection agents.