AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

Data Warehouse 91

Data Warehouse Snapshot Testing Management 91

AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 73

Data Warehouse Data-driven Snapshot Testing 73

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.

Data Warehouse 81

Data Warehouse Analytics Metrics Dashboards 81

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. Modern analytics is much wider than SQL-based data warehousing.

Analytics 92

Analytics Data Warehouse Testing Dashboards 92

AWS Big Data

MAY 30, 2023

resource(“dynamodb”) table = dynamodb.Table(dydb_lookup_table) response = table.scan() items = response[“Items”] jsondata = sc.parallelize(items) lookupDf = glueContext.read.json(jsondata) return lookupDf # Load the Amazon Kinesis data stream from Amazon Glue Data Catalog. def readDynamoDb(): dynamodb = boto3.resource(“dynamodb”)

Data Lake 77

Data Lake Data Analytics Analytics Data Processing 77

AWS Big Data

OCTOBER 20, 2023

You can have multiple internal applications such as databases, data warehouses, or other systems where DNS names are not publicly resolvable. You can now use MSK Connect to privately connect with databases, data warehouses, and other resources in your VPC to comply with your security needs.

Data Processing 83

Data Processing Snapshot Data Warehouse Management 83

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. BI aims to deliver straightforward snapshots of the current state of affairs to business managers.

Business Intelligence 142

Business Intelligence Dashboards Data mining OLAP 142

AWS Big Data

JANUARY 24, 2023

Data migration must be performed separately using methods such as S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication. This utility has two modes for replicating Lake Formation and Data Catalog metadata: on-demand and real-time. Nivas Shankar is a Principal Product Manager for AWS Lake Formation.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Clustering data for better data colocation using z-ordering.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. This post is designed to be implemented for a real customer use case, where you get full snapshot data on a daily basis. He helps customers implement Big Data and Analytics Solutions.

Data Lake 68

Data Lake Testing Snapshot Sales 68

AWS Big Data

MARCH 3, 2023

Any time new test cases or test results are created or modified, events trigger such that processing is immediate and new snapshot files are available via an API or data is pulled at the refresh frequency of the reporting or business intelligence (BI) tool. Ricardo Serafim is a Senior AWS Data Lab Solutions Architect.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

AUGUST 16, 2023

Time travel Time travel queries in Athena query Amazon S3 for historical data from a consistent snapshot as of a specified date and time. Version travel queries in Athena query Amazon S3 for historical data as of a specified snapshot ID. Karthikeyan Ramachandran is a Data Architect with AWS Professional Services.

Data Lake 68

Data Lake Metadata Testing Snapshot 68

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 79

Data Lake Dashboards Metrics Metadata 79

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes.

OLAP 90

OLAP Data Lake Data-driven Snapshot 90