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 103

Analytics IT Data Lake Visualization 103

AWS Big Data

MARCH 29, 2024

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. QuickSight periodically runs Amazon Athena queries to load query results to SPICE and then visualize the latest metric data. The filtered Worker Utilization per Job visualization shows 0.5,

Metrics 113

Metrics Visualization Dashboards Interactive 113

DataKitchen

JANUARY 3, 2022

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. In business analytics, fire-fighting and stress are common. Analytics Hub and Spoke.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

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).

Data Lake 105

Data Lake Data Warehouse Testing Business Objectives 105

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 83

Data Warehouse Sales Visualization Data Processing 83

AWS Big Data

DECEMBER 5, 2023

This dynamic tool, powered by AWS and CARTO, provided robust visualizations of which regions and populations were interacting with our survey, enabling us to zoom in quickly and address gaps in coverage. This cut down significantly on analytical turnaround times.

Measurement 88

Measurement Dashboards Data Warehouse Analytics 88

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a unified view of all data. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 320

Management Data Warehouse Data Quality Data Integration 320

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

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 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

JUNE 28, 2023

For example, customers told us that they want to ingest streaming data into their data stores for doing analytics—all without delving into the complexities of ETL. They can connect to multiple data streams and pull data directly into Amazon Redshift without staging it in Amazon Simple Storage Service (Amazon S3).

Analytics 72

Analytics Data Warehouse Data Lake Data-driven 72

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

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 119

Analytics IoT Data-driven Snapshot 119

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 103

Data Governance Unstructured Data Metadata Data Lake 103

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. The following is a visual representation of an example job where the number of workers is 10.

Metrics 103

Metrics Data Lake Cost-Benefit Dashboards 103

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

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 91

Enterprise Data Warehouse Snapshot Cost-Benefit 91

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. This is Now.

Data Warehouse 92

Data Warehouse Machine Learning Visualization Data Lake 92

AWS Big Data

MARCH 25, 2024

To understand the best ways to make API calls via Apache Flink, refer to Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 98

Data Lake Unstructured Data Management Modeling 98

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. The extracted data is stored in Amazon S3, which serves as the data lake.

Data Quality 71

Data Quality Data Lake Visualization Data-driven 71

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. Data mining. Visual Analytics and Data Visualization.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Visual Studio Online. Here they are in my order of importance (based upon my opinion).

Data Science 106

Data Science Machine Learning Data Lake IoT 106

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

Jen Stirrup

MAY 5, 2020

Organizations need to recast storing their data. It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. Using open-source analytics means you can spin up significant clusters as and when you need them.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. Particularly those on the “the create side of the house” who are tasked to deliver insights and analytics. Such inconsistencies bring lowered trust in the outcomes analytics and insights leaders try to get. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning.

Data Quality 96

Data Quality Statistics Data Lake Visualization 96

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Analyst.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

JANUARY 15, 2021

As Microsoft focuses its reporting strategy around Power BI and Azure Data Lake services, Dynamics partners should carefully consider the implications of starting down the path that Microsoft is recommending. Jet Analytics is a complete reporting and analytics platform that works with the entire family of Microsoft Dynamics products.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML).

Data Lake 81

Data Lake Data Warehouse Sales Data-driven 81

Sisense

OCTOBER 6, 2020

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data. Why is quantitative data important?

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 108

Data Warehouse Data Lake Analytics Machine Learning 108

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 99

Data Analytics Analytics Data Warehouse Data Lake 99

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Andrew White

OCTOBER 22, 2021

Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Chief Data Strategist 1.

IT 52

IT Data Lake Strategy Data Science 52