Remove Data mining Remove Statistics Remove Unstructured Data Remove Visualization
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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. In some ways, the data architect is an advanced data engineer.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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What is data science? Transforming data into value

CIO Business Intelligence

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Tableau: Now owned by Salesforce, Tableau is a data visualization tool.

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

CIO Business Intelligence

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer vs. data architect.

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Business Intelligence vs Data Science vs Data Analytics

FineReport

Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information. Typical tools for data science: SAS, Python, R.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

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Text Analytics – Understanding the Voice of Consumers

BizAcuity

Over the decade’s Hospitality Industry wings expand to the new horizon due to the widespread usage of mobiles which allows customers to plan the vacation & visualize the ambiance at their fingertips. Text analytics helps to draw the insights from the unstructured data. .