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

AWS Big Data

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 113
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7 key Microsoft Azure analytics services (plus one extra)

CIO Business Intelligence

Azure Data Factory. Azure Data Explorer is used to store and query data in services such as Microsoft Purview, Microsoft Defender for Endpoint, Microsoft Sentinel, and Log Analytics in Azure Monitor. Azure Data Lake Analytics.

Data Lake 111
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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. Google launches BigQuery, its own data warehousing tool and Microsoft introduces Azure SQL Data Warehouse and Azure Data Lake Store.

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It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

It also revealed that only 37 percent of organisational data being stored in cloud data warehouses, and 35 percent still in on-premises data warehouses. However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years. zettabytes of data. Oil and Gas.

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A hybrid approach in healthcare data warehousing with Amazon Redshift

AWS Big Data

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

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What is a Data Pipeline?

Jet Global

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.