Remove insights cloud-data-analytics choosing-the-best-data-analytics-tools
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What is a business intelligence analyst? A key role for data-driven decisions

CIO Business Intelligence

Business intelligence (BI) analysts transform data into insights that drive business value. The role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect through business intelligence strategies. What does a business intelligence analyst do?

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Successfully conduct a proof of concept in Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The scope should contain inputs and data points on the current architecture as well as the target architecture.

Testing 98
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Visualize Amazon DynamoDB insights in Amazon QuickSight using the Amazon Athena DynamoDB connector and AWS Glue

AWS Big Data

DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data import and export tools. The scalability and flexible data schema of DynamoDB make it well-suited for a variety of use cases. QuickSight uses the Athena connector to visualize BI insights from DynamoDB.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

Does data excite, inspire, or even amaze you? Moreover, companies that use BI analytics are five times more likely to make swifter, more informed decisions. Table of Contents. 1) Why Shift To A BI Career? 2) Top 10 Necessary BI Skills. 3) What Are the First Steps To Getting Started? 4) Business Intelligence Job Roles. It’s Flexible.

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Top 10 Big Data CRM Tools To Increase Business Sales

Smart Data Collective

Big data technology is incredibly important in modern business. One of the most important applications of big data is with building relationships with customers. These software tools rely on sophisticated big data algorithms and allow companies to boost their sales, business productivity and customer retention.

Sales 141
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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

AWS Big Data

We’re living in the age of real-time data and insights, driven by low-latency data streaming applications. The volume of time-sensitive data produced is increasing rapidly, with different formats of data being introduced across new businesses and customer use cases.

Analytics 111