AWS Big Data

MAY 29, 2024

User3 is a Business Analyst who needs to query data stored in Amazon Redshift tables using the Amazon Redshift Query Editor v2. Additionally, this user builds Amazon QuickSight visualizations for the data in Redshift tables. Refer to Configure SAML and SCIM with Okta and IAM Identity Center for instructions.

Data Lake 72

Data Lake Enterprise Management Business Intelligence 72

AWS Big Data

MARCH 27, 2023

In this post, we demonstrate how Amazon Athena , Amazon QuickSight , and Confluent work together to enable visualization of data streams in near-real time. Data visualization for Confluent data A frequent use case for enterprises is data visualization.

Visualization 78

Visualization Data Lake Interactive Data-driven 78

Jet Global

SEPTEMBER 4, 2020

Its solution was to replicate data from the production database, using data entities, into a traditional relational database. Microsoft referred to this approach as “bring your own database” (BYOD). There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”). Data Lakes.

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Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 115

Data Lake Analytics Dashboards Metrics 115

AWS Big Data

JUNE 6, 2023

It provides insights and metrics related to the performance and effectiveness of data quality processes. In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner.

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

Alation

FEBRUARY 20, 2020

The result, as many industry observers have put it, is that many data lakes become data swamps. New data visualization user interfaces from Tableau and Qlik proved that any business user can analyze their own data. Get the latest data cataloging news and trends in your inbox.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

AWS Big Data

JANUARY 26, 2023

AWS Glue provides an extensible architecture that enables users with different data processing use cases. A common use case is building data lakes on Amazon Simple Storage Service (Amazon S3) using AWS Glue extract, transform, and load (ETL) jobs. AWS Glue version Hudi Delta Lake Iceberg AWS Glue 3.0 AWS Glue 4.0

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Data Lake Big Data Software Interactive 113

AWS Big Data

JANUARY 12, 2024

Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

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Data Lake Cost-Benefit Visualization Structured Data 96

AWS Big Data

NOVEMBER 6, 2023

Amazon EMR Studio is an integrated development environment (IDE) that makes it straightforward for data scientists and data engineers to develop, visualize, and debug data engineering and data science applications written in R, Python, Scala, and PySpark. This helps you reduce operational overhead.

Data Lake 96

Data Lake Sales Management Testing 96

AWS Big Data

JUNE 6, 2023

It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines. Data quality at rest focuses on validating the data stored in data lakes, databases, or data warehouses. It ensures that the data meets specific quality standards before it is consumed.

Data Quality 71

Data Quality Data Lake Visualization Data-driven 71

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. In some ways, the data architect is an advanced data engineer.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. The following is a visual representation of an example job where the number of workers is 10. workerUtilization showed 1.0 100%) based on the workload requirements.

Metrics 97

Metrics Data Lake Cost-Benefit Dashboards 97

AWS Big Data

JANUARY 18, 2024

AWS Lake Formation and the AWS Glue Data Catalog form an integral part of a data governance solution for data lakes built on Amazon Simple Storage Service (Amazon S3) with multiple AWS analytics services integrating with them. To learn more about DataZone, refer to the User Guide. Bienvenue dans DataZone!

Data Lake 92

Data Lake Metadata Data Governance Statistics 92

DataKitchen

JUNE 12, 2023

I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science. Today we have had over 20,000 signatures , millions of page views, and copycat clones, and it is frequently used as a reference guide. It’s Customer Journey for data analytic systems.

Testing 130

Testing Data Lake Dashboards Data Science 130

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. Today, we are pleased to announce a new and enhanced visual job authoring capabilities for Amazon Redshift ETL and ELT workflows on the AWS Glue Studio visual editor.

Visualization 81

Visualization Data Warehouse Big Data Data Lake 81

AWS Big Data

OCTOBER 23, 2023

Modern applications store massive amounts of data on Amazon Simple Storage Service (Amazon S3) data lakes, providing cost-effective and highly durable storage, and allowing you to run analytics and machine learning (ML) from your data lake to generate insights on your data.

Data Lake 104

Data Lake Visualization Optimization Interactive 104

AWS Big Data

MAY 16, 2024

However, visualizing and analyzing large-scale geospatial data presents a formidable challenge due to the sheer volume and intricacy of information. This often overwhelms traditional visualization tools and methods. Figure 1 – Map built with CARTO Builder and the native support to visualize H3 indexes What are spatial indexes?

Data Warehouse 109

Data Warehouse Visualization Cost-Benefit Optimization 109

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Choose Create endpoint.

Data Lake 100

Data Lake Data Warehouse Testing Business Objectives 100

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

AWS Big Data

MARCH 27, 2024

These services enable you to collect and analyze data in near real time and put a comprehensive data governance framework in place that uses granular access control to secure sensitive data from unauthorized users. To create an AWS HealthLake data store, refer to Getting started with AWS HealthLake.

Data Analytics 93

Data Analytics Analytics Data Warehouse Data Lake 93

AWS Big Data

MARCH 25, 2024

To learn more about RAG, refer to Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart. A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

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Data Warehouse Data Lake Visualization Big Data 131

AWS Big Data

MARCH 18, 2024

To create your namespace and workgroup, refer to Creating a data warehouse with Amazon Redshift Serverless. Use Query Editor v2 to load customer data from Amazon S3 You can use Query Editor v2 to submit queries and load data to your data warehouse through a web interface.

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Data Warehouse Visualization Snapshot Data-driven 83

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. Choose Create job and Visual ETL. Choose Create connection.

Analytics 98

Analytics IT Data Lake Visualization 98

AWS Big Data

NOVEMBER 20, 2023

The serverless Spark UI parses a Spark event log file generated in your S3 bucket to visualize detailed information for both running and completed job runs. For more information about Apache Spark UI, refer to Web UI in Apache Spark. The following screen capture shows a sample visual job authored in AWS Glue Studio visual editor.

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Visualization Optimization Data Lake Management 88

AWS Big Data

NOVEMBER 29, 2023

For more information about performance improvement capabilities, refer to the list of announcements below. Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications.

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Data Warehouse Data Lake Analytics Machine Learning 103

AWS Big Data

JUNE 21, 2023

When setting out to build a data warehouse, it’s a common pattern to have a data lake as the source of the data warehouse. The data lake in this context serves a number of important functions: It acts as a central source for multiple applications, not just exclusively for data warehousing purposes.

Data Warehouse 82

Data Warehouse Data Lake OLAP Cost-Benefit 82

CIO Business Intelligence

JUNE 29, 2022

Data Explorer is a big data analytics platform that you can use, as the name suggests, for exploring data using KQL, also known as the Kusto Query Language, from the codename for the project which may or may not be a reference to exploring your ocean of data as if you were Jacques Cousteau. Everything is visual.

Data Lake 110

Data Lake Analytics Data Warehouse Machine Learning 110

Jet Global

MAY 9, 2024

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.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

DECEMBER 18, 2023

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue , Amazon EMR , and Amazon Redshift. There are multiple tables related to customers and order data in the RDS database.

Metadata 123

Metadata Visualization Data Lake Data-driven 123

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

Data Lake 79

Data Lake Testing Interactive Unstructured Data 79

AWS Big Data

MAY 23, 2024

We also show how to take action based on the data quality results. Solution overview Let’s consider an example data quality pipeline where a data engineer ingests data from a raw zone and loads it into a curated zone in a data lake. For more information, refer to Dynamic rules. Choose Save.

Data Quality 88

Data Quality Metrics Data Lake Sales 88

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

AWS Big Data

MARCH 26, 2024

It is prudent to consolidate this data into a single customer view, serving as a primary reference for downstream applications, ranging from ecommerce platforms to CRM systems. This consolidated view acts as a liaison between the data platform and customer-centric applications.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

NOVEMBER 30, 2023

With AWS Glue, you can discover and connect to more than 100 diverse data sources and manage your data in a centralized data catalog. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes. Choose Visual ETL.

IT 98

IT Visualization Machine Learning Data Integration 98

AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.

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Insurance Visualization Data Lake Metrics 83

AWS Big Data

JANUARY 8, 2024

For security, Kinesis Data Streams provide server-side encryption so you can meet strict data management requirements by encrypting your data at rest and Amazon Virtual Private Cloud (VPC) interface endpoints to keep traffic between your Amazon VPC and Kinesis Data Streams private.

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Analytics IoT Data-driven Snapshot 115