AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 103

Data Warehouse Snapshot Data Processing Management 103

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. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 100

Analytics IT Data Lake Visualization 100

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 117

Data Lake Analytics Dashboards Metrics 117

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. This is the essence of Convergent Evolution. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 78

Data Lake Data Warehouse Sales Data-driven 78

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. He is passionate about big data and data analytics. He helps enterprise customers migrate and modernize their data lake and data warehouse using AWS services.

Metadata 80

Metadata Testing Data Lake Consulting 80

AWS Big Data

MAY 10, 2023

A write-back is the ability to update a data mart, data warehouse, or any other database backend from within BI dashboards and analyze the updated data in near-real time within the dashboard itself. AnyCompany currently uses Amazon Redshift as their enterprise data warehouse platform and QuickSight as their BI solution.

Dashboards 77

Dashboards Data Warehouse Visualization Data Processing 77

Howard Dresner

JANUARY 8, 2013

December 18, 2012 Dresner’s Point: Will Amazon’s Redshift Become a BI Swiss Army Knife? BIWisdom tweetchat tribe members were facing off in response to the question of whether the EDW (electronic data warehouse) is dead. December 11, 2012 Dresner’s Point: What’s Innovation Worth in BI? Once upon a time.

Business Intelligence 45

Business Intelligence Data Warehouse Data Processing Big Data 45

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 88

Data Warehouse Analytics Metrics Dashboards 88

AWS Big Data

JUNE 6, 2023

Founded in 2012, SumUp is the financial partner for more than 4 million small merchants in over 35 markets worldwide, helping them start, run and grow their business. Unless, of course, the rest of their data also resides in the Google Cloud. This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp.

Analytics 57

Analytics Data Lake Testing Optimization 57

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Most of the data management moved to back-end servers, e.g., databases.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

APRIL 30, 2024

It can generate data integration jobs for extracts and loads to S3 data lakes including file formats like CSV, JSON, and Parquet, and ingestion into open table formats like Apache Hudi, Delta, and Apache Iceberg. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Data Integration 108

Data Integration Data Lake Data Warehouse Software 108

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse.

Analytics 70

Analytics Data Warehouse Optimization Metrics 70

Cloudera

MAY 10, 2018

Cloudera 2017 Data Impact Award Winners. We are excited to kick off the 2018 Data Impact Awards ! Since 2012, the Data Impact Awards have showcased how organizations are using Cloudera and the power of data to transform themselves and achieve dramatic results.

Machine Learning 41

Machine Learning Predictive Analytics Data-driven Data Science 41

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage.

Data Warehouse 92

Data Warehouse Metrics Statistics Optimization 92

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Interesting times.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

IBM Big Data Hub

JANUARY 10, 2023

This allows data that exists in cloud object storage to be easily combined with existing data warehouse data without data movement. The advantage to NPS clients is that they can store infrequently used data in a cost-effective manner without having to move that data into a physical data warehouse table.

Data Warehouse 52

Data Warehouse Cost-Benefit Statistics Data Processing 52

Smart Data Collective

OCTOBER 17, 2022

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

Big Data 105

Big Data Data-driven Recreation/Entertainment Data Governance 105

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 105

Data Lake Data Warehouse Management Risk 105

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. That was the origin of big data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

BizAcuity

MAY 10, 2022

2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. An efficient big data management and storage solution that AWS quickly took advantage of. They now have a disruptive data management solution to offer to its client base.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

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.

Management 94

Management Data Lake Sales Data Warehouse 94

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 88

Machine Learning Metrics Management Big Data 88

AWS Big Data

NOVEMBER 30, 2023

This integration simplifies the authentication and authorization process for Amazon Redshift users using Query Editor V2 or Amazon Quicksight , making it easier for them to securely access your data warehouse. Note: Your organization’s IdC instance must be in the same region as the Amazon Redshift data warehouse you’re connecting to.

Data Warehouse 85

Data Warehouse Finance Sales Management 85

AWS Big Data

DECEMBER 12, 2023

Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries. You can use your preferred SQL clients to analyze your data in an Amazon Redshift data warehouse. He is passionate about automating and solving customer problems with cloud solutions.

Data Warehouse 100

Data Warehouse Management Finance Analytics 100

AWS Big Data

MAY 4, 2023

Amazon Redshift Serverless makes it easy to run and scale analytics in seconds without the need to set up and manage data warehouse clusters. Customers use their preferred SQL clients to analyze their data in Redshift Serverless. An Redshift Serverless data warehouse. If you don’t have one, you can sign up for one.

Finance 82

Finance Data Warehouse Sales Metadata 82

AWS Big Data

MARCH 21, 2023

In this post, we discuss how to democratize data access to Amazon Redshift using the Amazon Redshift Query Editor V2. Background At AWS Payments, we had been using Redash to allow our users to author and run SQL queries against our Amazon Redshift data warehouse.

Cost-Benefit 75

Cost-Benefit Dashboards Visualization Data-driven 75

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools.

Data Lake 67

Data Lake Data Governance Data Warehouse Modeling 67