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 69

Data Quality Metrics Visualization Dashboards 69

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 90

Data Lake Unstructured Data Management Modeling 90

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. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 88

Data Lake Data Warehouse Data-driven B2B 88

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 77

Metrics Data Warehouse Dashboards Snapshot 77

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 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

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 122

Data Warehouse Business Driver Data Lake Data-driven 122

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 144

Machine Learning Cost-Benefit Data-driven Strategy 144

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. You can subscribe to data products that help enrich customer profiles, for example demographics data, advertising data, and financial markets data. Data processing Raw data is often cluttered with duplicates and irregular formats.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

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 111

Analytics IoT Data-driven Snapshot 111

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

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 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

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 121

Cost-Benefit Internet of Things Data-driven Data Lake 121

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 104

Data Warehouse Testing Data Quality Reporting 104

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

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 67

Reporting Metrics Optimization Data Lake 67

Cloudera

JUNE 16, 2022

The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities. Apache Flink is a distributed processing engine for stateful computations ideally suited for real-time, event-driven applications.

Data Lake 85

Data Lake Manufacturing Metadata Dashboards 85

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

CIO Business Intelligence

SEPTEMBER 21, 2022

“The good news for many CIOs is that they’ve already laid the groundwork through investments in data governance and migration to the cloud,” LiveRamp noted in a recent report. CEO & CFO – “Bring your stakeholders along your journey, proving your strategy’s value by being transparent on the metrics you’re tracking and how you’re faring.

Risk 102

Risk Data Lake Marketing Interactive 102

IBM Big Data Hub

SEPTEMBER 19, 2023

Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred. The dedicated data analyst Virtually any stakeholder of any discipline can analyze data. They may also use tools such as Excel to sort, calculate and visualize data. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

AWS Big Data

JULY 12, 2023

Organizations use their data to extract valuable insights and drive informed business decisions. Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse. Etleap simplifies the data pipeline building experience.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

Cloudera

OCTOBER 25, 2022

Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses. They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

AWS Big Data

JUNE 6, 2023

You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions. Choose Save ruleset.

Data Quality 72

Data Quality Data Lake Data-driven Metrics 72

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective.

Enterprise 48

Enterprise Data Lake Data mining IoT 48

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 Cost-Benefit 150

IBM Big Data Hub

OCTOBER 16, 2023

ML also provides the ability to closely monitor a campaign by checking open and clickthrough rates, among other metrics. ML classification algorithms are also used to label events as fraud, classify phishing attacks and more. Then, it can tailor marketing materials to match those interests.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

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 82

Machine Learning Metrics Management Big Data 82

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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