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.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

JUNE 10, 2024

For detailed information on managing your Apache Hive metastore using Lake Formation permissions, refer to Query your Apache Hive metastore with AWS Lake Formation permissions. In this post, we present a methodology for deploying a data mesh consisting of multiple Hive data warehouses across EMR clusters.

Data Lake 88

Data Lake Metadata Data Warehouse Data Processing 88

AWS Big Data

FEBRUARY 24, 2023

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. A data lake built on AWS uses Amazon Simple Storage Service (Amazon S3) as its primary storage environment.

Data Lake 82

Data Lake Metadata Testing Data Warehouse 82

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. For more information, refer to Retry Amazon S3 requests with EMRFS. availability.

Data Lake 83

Data Lake Snapshot Metadata Optimization 83

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 73

Data Lake Testing Snapshot Big Data 73

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

Data Lake 85

Data Lake Data Warehouse Marketing Management 85

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 115

Optimization Snapshot Data Lake Metadata 115

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 72

Data Lake Snapshot Optimization Data Transformation 72

DataKitchen

OCTOBER 11, 2021

The data engineer then emails the BI Team, who refreshes a Tableau dashboard. Figure 1: Example data pipeline with manual processes. There are no automated tests , so errors frequently pass through the pipeline. Figure 2: Example data pipeline with DataOps automation. Adding Tests to Reduce Stress.

Testing 162

Testing Metadata Dashboards Statistics 162

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 Dashboards Data Lake Data Science 130

AWS Big Data

NOVEMBER 26, 2024

Initially, data warehouses were the go-to solution for structured data and analytical workloads but were limited by proprietary storage formats and their inability to handle unstructured data. Eventually, transactional data lakes emerged to add transactional consistency and performance of a data warehouse to the data lake.

Metadata 86

Metadata Data Lake Snapshot Data Warehouse 86

AWS Big Data

NOVEMBER 6, 2023

You can attach an EMR Studio Workspace to an EMR cluster, and use the compute power of the EMR cluster and run data science jobs on the cluster. Data is often stored in data lakes managed by AWS Lake Formation , enabling you to apply fine-grained access control through a simple grant or revoke mechanism.

Data Lake 98

Data Lake Sales Management Testing 98

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

Snapshot 115

Snapshot Data Lake Metadata Recreation/Entertainment 115

AWS Big Data

JULY 3, 2023

Major market indexes, such as S&P 500, are subject to periodic inclusions and exclusions for reasons beyond the scope of this post (for an example, refer to CoStar Group, Invitation Homes Set to Join S&P 500; Others to Join S&P 100, S&P MidCap 400, and S&P SmallCap 600 ).

Snapshot 86

Snapshot Data Lake Testing Strategy 86

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 95

Data Quality Data Governance Data Lake Testing 95

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 103

Data Lake Cost-Benefit Data-driven Data Warehouse 103

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

MAY 29, 2024

Refer to Configure SAML and SCIM with Okta and IAM Identity Center for instructions. You need to reference the bucket name and the certificate bundle.zip file in AWS CloudFormation. Refer to the following table for a list of important parameters. In this post, we use the us-east-1 Region. In this post, we grant access to Group1.

Data Lake 86

Data Lake Enterprise Management Business Intelligence 86

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Compare ongoing data that is replicated from the source on-premises database to the target S3 data lake.

Data Quality 88

Data Quality Data Lake Data Warehouse Metrics 88

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.

Data Warehouse 134

Data Warehouse Data Lake Visualization Big Data 134

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 103

Data Lake Data Warehouse Testing Business Objectives 103

AWS Big Data

AUGUST 5, 2024

These business units have varying landscapes, where a data lake is managed by Amazon Simple Storage Service (Amazon S3) and analytics workloads are run on Amazon Redshift , a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Data Lake 87

Data Lake Finance Sales Management 87

AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 73

Data Lake Data Warehouse Data-driven Optimization 73

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. Enabling automatic compaction on Iceberg tables reduces metadata overhead on your Iceberg tables and improves query performance.

Data Lake 84

Data Lake IoT Metadata Testing 84

AWS Big Data

SEPTEMBER 4, 2024

This solution also allows you to update certain fields of the account object in the data lake and push it back to Salesforce. To achieve this, you create two ETL jobs using AWS Glue with the Salesforce connector, and create a transactional data lake on Amazon S3 using Apache Iceberg.

Data Integration 82

Data Integration Data Lake Data-driven Cost-Benefit 82

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 88

Data Lake Big Data Consulting Data Warehouse 88

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Testing 104

Testing Data Warehouse Metrics Cost-Benefit 104

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 97

Data Analytics Analytics Data Warehouse Data Lake 97

AWS Big Data

NOVEMBER 10, 2023

These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. During feature development, data engineers require a seamless interface to the EDW. Previous solution process In the previous solution, product team data engineers spent 30 minutes per run to manually expose Redshift data to Spark.

Data Processing 97

Data Processing Data Lake Data Warehouse Optimization 97

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 100

Data Warehouse Testing Data Lake Data-driven 100

CIO Business Intelligence

AUGUST 9, 2024

If after anonymization the level of information in the data is the same, the data is still useful. But once personal or sensitive references are removed, and the data is no longer effective, a problem arises. Synthetic data avoids these difficulties, but they’re not exempt from the need of a trade-off.

Risk 138

Risk Measurement Data Lake Data Collection 138

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 75

Data Lake Testing Interactive Unstructured Data 75

AWS Big Data

JUNE 8, 2023

For instructions, refer to Creating and managing Amazon OpenSearch Service domains. Choose Send test message and test to make sure you receive an alert on the PagerDuty service. This notification can be safely acknowledged and resolved from PagerDuty because this is was a test.

Data Lake 78

Data Lake Dashboards Metrics Testing 78

AWS Big Data

APRIL 26, 2024

Use Lake Formation to grant permissions to users to access data. Test the solution by accessing data with a corporate identity. Audit user data access. For a complete guide on creating and providing a certificate, refer to Providing certificates for encrypting data in transit with Amazon EMR encryption.

Analytics 100

Analytics Data Lake Management Enterprise 100

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 107

Data Lake Visualization Optimization Interactive 107

AWS Big Data

NOVEMBER 29, 2023

For more information about performance improvement capabilities, refer to the list of announcements below. Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse.

Data Warehouse 104

Data Warehouse Analytics Data Lake Machine Learning 104

AWS Big Data

FEBRUARY 15, 2024

You might be modernizing your data architecture using Amazon Redshift to enable access to your data lake and data in your data warehouse, and are looking for a centralized and scalable way to define and manage the data access based on IdP identities. For IAM role , choose a Lake Formation user-defined role.

Management 94

Management Data Lake Sales Data Warehouse 94