Remove data databases how-does-indexing-work
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Take Your SQL Skills To The Next Level With These Popular SQL Books

datapine

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

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Comparing DynamoDB and MongoDB for Big Data Management

Smart Data Collective

A growing number of companies are discovering the benefits of investing in big data technology. Companies around the world spent over $160 billion on big data technology last year and that figure is projected to grow 11% a year for the foreseeable future. Unfortunately, big data technology is not without its challenges.

Big Data 110
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Try semantic search with the Amazon OpenSearch Service vector engine

AWS Big Data

Background A search engine is a special kind of database, allowing you to store documents and data and then run queries to retrieve the most relevant ones. Textual vector search The demo of textual vector search shows how vector embeddings can capture the context of your query beyond just the words that compose it.

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Data-Centric Firms Address Athena Shortcomings with Smart Indexing

Smart Data Collective

There are a lot of benefits of data scalability. The size and the variety of data that enterprises have to deal with have become more complex and larger. Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. Indexing capabilities. AWS Athena and S3.

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The road to Software 2.0

O'Reilly on Data

The process is slow, tedious, and error-prone; most of us have spent days staring at a program that should work, but doesn’t. Nor are building data pipelines and deploying ML systems well understood. The companies that are systematizing how they develop ML and AI applications are companies that already have advanced AI practices.

Software 261
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Enable cost-efficient operational analytics with Amazon OpenSearch Ingestion

AWS Big Data

A few of the defining characteristics of these use cases are ingesting a high volume of time series data and a relatively low volume of querying, alerting, and running analytics on ingested data for real-time insights. The time series data often contains logs or telemetry data from various sources with different values and needs.

Analytics 117
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Extend geospatial queries in Amazon Athena with UDFs and AWS Lambda

AWS Big Data

Amazon Athena is a serverless and interactive query service that allows you to easily analyze data in Amazon Simple Storage Service (Amazon S3) and 25-plus data sources, including on-premises data sources or other cloud systems using SQL or Python. For Bucket name , enter a globally unique name for your data bucket.