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SQL Streambuilder Data Transformations

Cloudera

As an essential part of ETL, as data is being consolidated, we will notice that data from different sources are structured in different formats. It might be required to enhance, sanitize, and prepare data so that data is fit for consumption by the SQL engine. What is a data transformation?

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

In addition to driving operational efficiency and consistently meeting fulfillment targets, logistics providers use big data applications to provide real-time updates as well as a host of flexible pick-up, drop-off, or ordering options. Like many modern sectors, logistics processes involve large amounts of data collection.

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

AWS Big Data

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches.

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Enable advanced search capabilities for Amazon Keyspaces data by integrating with Amazon OpenSearch Service

AWS Big Data

It empowers businesses to explore and gain insights from large volumes of data quickly. Amazon OpenSearch Ingestion is a fully managed, serverless data collection solution that efficiently routes data to your OpenSearch Service domains and Amazon OpenSearch Serverless collections.

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The Modern Data Stack Explained: What The Future Holds

Alation

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. Examples of data transformation tools include dbt and dataform.

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Addressing the Three Scalability Challenges in Modern Data Platforms

Cloudera

In addition, more data is becoming available for processing / enrichment of existing and new use cases e.g., recently we have experienced a rapid growth in data collection at the edge and an increase in availability of frameworks for processing that data. Limited flexibility to use more complex hosting models (e.g.,

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What Is Embedded Analytics?

Jet Global

Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.” addresses).