AWS Big Data

DECEMBER 18, 2023

Amazon Redshift empowers users to extract powerful insights by securely and cost-effectively analyzing data across data warehouses, operational databases, data lakes, third-party data stores, and streaming sources using zero-ETL approaches.

Data Warehouse 100

Data Warehouse Machine Learning Data-driven Data Lake 100

CIO Business Intelligence

SEPTEMBER 12, 2022

Fazal and his team have moved most of NJ Transit’s data to the cloud, evolving from simple reports to advanced analytics and AI/ML models that generate insights that transportation business analysts could only dream about in the past, he says. “We As a result, NJ Transit’s data maturity as an organization has grown.

Data Warehouse 113

Data Warehouse Predictive Analytics Data Lake IoT 113

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics.

Management 66

Management Data Lake Uncertainty Data Warehouse 66

AWS Big Data

NOVEMBER 7, 2023

Now, as part of Infosys Cobalt and Infosys Topaz blueprints, enterprises can have near real-time analytics on transactional data, which can help them make informed decisions related to store management. Prior to his current role, he was VP of Analytics at AWS, where he worked across the entire AWS database portfolio.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

CIO Business Intelligence

DECEMBER 1, 2022

The $247 billion conglomerate, one of the largest food and beverage companies in the world, is developing a modernized data and cloud infrastructure replete with automated processes and workflows. One HR employee took some courses in data analytics and found a new job within the company helping to advance digital transformation. “I

Digital Transformation 120

Digital Transformation IoT Data-driven KPI 120

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. About the Authors Ismail Makhlouf is a Senior Specialist Solutions Architect for Data Analytics at AWS.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

MAY 16, 2024

About Amazon Redshift Thousands of customers rely on Amazon Redshift to analyze data from terabytes to petabytes and run complex analytical queries. With Amazon Redshift, you can get real-time insights and predictive analytics on all of your data across your operational databases, data lake, data warehouse, and third-party datasets.

Data Warehouse 109

Data Warehouse Visualization Cost-Benefit Optimization 109

IBM Big Data Hub

DECEMBER 7, 2023

C-OLAP optimized data storage for faster query processing, while IM-OLAP stored data in memory to minimize data access latency and enable real-time analytics. Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

BizAcuity

MAY 16, 2022

The more effectively a company uses data, the better it performs. As a data analytics company, we have been observing a trend among certain large enterprises who are looking for real-time data streaming for analytics. So much so that they can predict certain aspects about their customers with high accuracy.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Overall, DataOps is an essential component of modern data-driven organizations. Query> DataOps. Query> Write an essay on DataOps.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Andrew White

JANUARY 11, 2021

Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? Data lakes don’t offer this nor should they. Governance. Product Management.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Modern businesses are increasingly leveraging analytics for a range of use cases. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. What is Data Analytics?

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

AWS Big Data

JULY 12, 2023

It automatically provisions and scales the data warehouse capacity to deliver high performance for demanding and unpredictable workloads, and you only pay for the resources you use. Amazon Redshift delivers up to five times better price performance than other cloud data warehouses out of the box and helps you keep costs predictable.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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. In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44