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Azure Databricks Cookbook: Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service
87% of respondents would recommend this to a friend
MXN 983
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Learn best practices for working with large datasets and productionizing end-to-end big data solutions
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What Stands Out
Product Details
- Learn to integrate with Azure Synapse Analytics, Cosmos DB, and Azure HDInsight Kafka Cluster to scale and analyze projects
- Use Databricks SQL for ad hoc queries on data lake and create dashboards
- Productionize a solution using CI/CD for deploying notebooks and Azure Databricks Service to various environments
- Create an Azure Databricks instance within Azure portal, Azure CLI, and ARM templates
- Explore jobs, stages, and tasks and understand Spark lazy evaluation in Delta tables
- Integrate Azure DevOps for version control, deploying, and productionizing solutions with CI/CD pipelines
| Publisher | Packt Publishing |
| Publication date | September 17, 2021 |
| Language | English |
| Print length | 452 pages |
| ISBN-10 | 1789809711 |
| ISBN-13 | 978-1789809718 |
| Item Weight | 1.8 pounds (820 grams) |
| Dimensions | 7.5 x 1.02 x 9.25 inches (19.1 x 2.6 x 23.5 cm) |
Who Should Buy?
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Data Scientists
Ideal for data scientists looking to enhance their analytics and machine learning projects using Apache Spark efficiently.
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Big Data Engineers
Beneficial for big data engineers who need to manage large datasets and perform real-time data processing and analytics.
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Business Analysts
Great for business analysts who require insights from big data, leveraging interactive notebooks for data visualization.
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Casual Users
Not suitable for casual users who require simple data analytics without the complexity of advanced data processing tools.
Product Description
Azure Databricks Cookbook: Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service
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Features & Benefits
- Accelerate and scale real-time analytics solutions using Azure Databricks
- Integrate with other Azure services to analyze and build pipelines
- Use Databricks SQL for ad hoc queries and create dashboards
- Productionize solutions using CI/CD to deploy notebooks and Databricks to different environments
- Suitable for data scientists, data engineers and big data professionals
- Prior experience with Apache Spark and Azure is required
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