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Introduction To The Basic Business Intelligence Concepts

datapine

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. They enable powerful data visualization.

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5 Pain Points of Moving Data to the Cloud and Strategies for Success

Alation

We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Accompanying this acceleration is the increasing complexity of data. Complex data management is on the rise.

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Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Operations data: Data generated from a set of operations such as orders, online transactions, competitor analytics, sales data, point of sales data, pricing data, etc. The gigantic evolution of structured, unstructured, and semi-structured data is referred to as Big data. Self-Service.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

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Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue

AWS Big Data

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. Navigate to the Visual tab.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

Visual layouts in some screenshots in this post may look different than those on your AWS Management Console. Data generation In this section, we discuss the steps to manually or automatically generate journey data. To query the data with Athena, complete the following steps: On the Athena console, open the query editor.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

Connecting the data in a graph allows concepts and entities to complement each other’s description. Given a critical mass of domain knowledge and good level of connectivity, KG can serve as context that helps computers comprehend and manipulate data. Make it easy to maintain and evolve your data fabric.