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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Build a transactional data lake using Apache Iceberg, AWS Glue, and cross-account data shares using AWS Lake Formation and Amazon Athena

AWS Big Data

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

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Detect, mask, and redact PII data using AWS Glue before loading into Amazon OpenSearch Service

AWS Big Data

Solution overview The following diagram illustrates the high-level solution architecture. We have defined all layers and components of our design in line with the AWS Well-Architected Framework Data Analytics Lens. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

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How Data Management and Big Data Analytics Speed Up Business Growth

BizAcuity

Its effective data analytics that allows personalization in marketing & sales, identifying new opportunities, making important decisions and being sustainable for the long term. Competitive Advantages to using Big Data Analytics. Data Management. Unscalable data architecture.

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Unstructured data management and governance using AWS AI/ML and analytics services

AWS Big Data

Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. Solution overview Data and metadata discovery is one of the primary requirements in data analytics, where data consumers explore what data is available and in what format, and then consume or query it for analysis.