AWS Big Data

JUNE 6, 2023

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

Data Quality 93

Data Quality Metrics Visualization Dashboards 93

AWS Big Data

FEBRUARY 12, 2024

About Redshift and some relevant features for the use case Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

Analytics 119

Analytics Data Warehouse Snapshot Cost-Benefit 119

AWS Big Data

APRIL 10, 2024

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Data Warehouse 118

Data Warehouse Analytics Metrics Snapshot 118

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 110

Data Warehouse Metrics Statistics Optimization 110

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. or higher version) database.

Data Warehouse 105

Data Warehouse Analytics Metrics Dashboards 105

AWS Big Data

JANUARY 15, 2025

AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster. The data in the central data warehouse in Amazon Redshift is then processed for analytical needs and the metadata is shared to the consumers through Amazon DataZone.

IoT 110

IoT Machine Learning Metadata Data-driven 110

CIO Business Intelligence

APRIL 12, 2023

Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool. Open the workgroup you want to monitor.

Metrics 97

Metrics Data Warehouse Dashboards Snapshot 97

CIO Business Intelligence

OCTOBER 19, 2023

Power BI is Microsoft’s interactive data visualization and analytics tool for business intelligence (BI). With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. You can also create manual metrics to update yourself.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

Analytics 93

Analytics Data Warehouse Data Lake Metadata 93

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

Data Warehouse 134

Data Warehouse Dashboards Risk Management Risk 134

AWS Big Data

FEBRUARY 26, 2025

This premier event showcased groundbreaking advancements, keynotes from AWS leadership, hands-on technical sessions, and exciting product launches. Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights.

Analytics 60

Analytics Data Lake Metadata Data Warehouse 60

AWS Big Data

MARCH 25, 2024

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

Data Lake 118

Data Lake Unstructured Data Management Snapshot 118

AWS Big Data

SEPTEMBER 11, 2024

The application supports custom workflows to allow demand and supply planning teams to collaborate, plan, source, and fulfill customer orders, then track fulfillment metrics via persona-based operational and management reports and dashboards. To achieve this, Aruba used Amazon S3 Event Notifications.

Data Architecture 109

Data Architecture Optimization Data Warehouse Metadata 109

AWS Big Data

MARCH 20, 2024

To run analytics on your operational data, you might build a solution that is a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 133

Data Warehouse Business Driver Data-driven Data Lake 133

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 109

Enterprise Data Warehouse Snapshot Cost-Benefit 109

AWS Big Data

JANUARY 8, 2024

It aims to provide a framework to create low-latency streaming applications on the AWS Cloud using Amazon Kinesis Data Streams and AWS purpose-built data analytics services. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 133

Analytics IoT Data-driven Snapshot 133

CIO Business Intelligence

SEPTEMBER 8, 2022

We’ve all experienced the pain of what continues to happen with the disconnect between customer usage metrics and gaps in supply chain data.” — Frank Cutitta ( @fcutitta ), CEO and Founder, HealthTech Decisions Lab “Operationally, think of logistics.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

AWS Big Data

SEPTEMBER 5, 2024

Federated queries allow querying data across Amazon RDS for MySQL and PostgreSQL data sources without the need for extract, transform, and load (ETL) pipelines. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

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 131

Data Lake Analytics Dashboards Metrics 131

Occam's Razor

JANUARY 30, 2012

When it comes to data analysis, you are usually more likely to see me share guidance on advanced segmentation or custom reports or advanced social metrics or controlled experiments or economic value or competitive intelligence or web analytics maturity or one of an infinite number of difficult, if hugely rewarding, things.

Analytics 146

Analytics Dashboards Metrics Key Performance Indicator 146

AWS Big Data

MAY 16, 2024

Zero-ETL will perform an initial full load of your collection by doing a collection scan on the primary instance of your Amazon DocumentDB cluster, which may take several minutes to complete depending on the size of the data, and you may notice elevated resource consumption on your cluster.

Data Processing 126

Data Processing Data Warehouse Management Dashboards 126

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

Smart Data Collective

FEBRUARY 20, 2022

Different DAM providers use different approaches to defining the key metrics that influence the cost of an off-the-shelf solution. On the one hand, the use of agents allows you to actively monitor and respond to events. There are different opinions. DAM deployment best practices. Let’s get to the bottom of this.

Behavioral Analytics 130

Behavioral Analytics Risk Machine Learning Interactive 130

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Cost-Benefit 94

Cost-Benefit IoT Data Warehouse Manufacturing 94

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption. EventBridge picks up the event from AWS Glue and triggers an AWS Lambda function.

Reporting 92

Reporting Metrics Optimization Data Lake 92

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Data-driven 150

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. However, throughout history, data services have held dominion over their customers’ data. They decided to focus on four runtime engines.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, 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 widely used cloud data warehouse.

Data Warehouse 98

Data Warehouse Analytics Metadata Dashboards 98

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 86

Data Warehouse Data Lake Cost-Benefit Metadata 86

Sisense

NOVEMBER 30, 2020

Some of the most common analytics and outcomes expected today: Visitor count and a history chart of visitor frequency (new sessions and return visitors) How content updates affected relevance Whether a predicted preference yielded an actual purchase Which performance metrics led to achieved goals. The impending data reality.

Analytics 98

Analytics Dashboards Metrics Data-driven 98

CIO Business Intelligence

NOVEMBER 29, 2022

Increasing data volumes and velocity can reduce the speed that teams make additions or changes to the analytical data structures at data integration points — where data is correlated from multiple different sources into high-value business assets. For data warehouses, it can be a wide column analytical table.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

Occam's Razor

MARCH 10, 2015

Dimension Widening – hello sweet simple data from spreadsheets, data warehouses/CRM systems! Measurement Protocol – all your data are belong to us! It is the simple, but powerful, ability to send data into Google Analytics to enrich your understanding performance. el (label): The name of the event.

Strategy 153

Strategy Analytics Measurement Business Analysis 153

Sisense

DECEMBER 23, 2019

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. There just aren’t enough AI and data science practitioners to go around to tackle this lofty goal. Apply that metric to any other business-critical function.

Data Lake 86

Data Lake Machine Learning Data Warehouse Data Science 86

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Sisense

MARCH 6, 2019

The crowd who attends these events are made mostly of analytics leaders in Enterprises. It’s always fun and insightful to be able to talk to so many CDOs, CIOs, data and BI professionals within 2.5 Part of the justification Gartner puts behind this is that metrics need to be constantly challenged.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75