Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

IBM Journey to AI blog

MAY 9, 2023

. “The media and entertainment industry has undergone a significant digital transformation, with viewers consuming content across different devices and platforms,” said Vitaly Tsivin, EVP Business Intelligence at AMC Networks. The solution will also be available in AWS Marketplace.

Data Warehouse 92

Data Warehouse AWS AI AI 92

AWS Machine Learning Blog

APRIL 12, 2023

In this post, we describe how AWS Partner Airis Solutions used Amazon Lookout for Equipment , AWS Internet of Things (IoT) services, and CloudRail sensor technologies to provide a state-of-the-art solution to address these challenges. It’s an easy way to run analytics on IoT data to gain accurate insights.

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phData

FEBRUARY 21, 2025

A data warehouse acts as a single source of truth for an organization’s data, providing a unified view of its operations and enabling data-driven decision-making. A data warehouse enables advanced analytics, reporting, and business intelligence. Data integrations and pipelines can also impact latency.

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Pickl AI

APRIL 9, 2025

This stage involves optimizing the data for querying and analysis. This process ensures that organizations can consolidate disparate data sources into a unified repository for analytics and reporting, thereby enhancing business intelligence. Integration capabilities are crucial for leveraging cloud services.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Smart Data Collective

APRIL 29, 2020

Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data management approaches are varied and may be categorised in the following: Cloud data management. Master data management. SharePoint.

Data Warehouse 97

Data Warehouse SQL Azure ETL 97

IBM Journey to AI blog

JULY 11, 2023

Data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics that enable faster decision making and insights.

Data Warehouse 60

Data Warehouse Database Cloud Data Big Data 60

ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Precisely

MARCH 14, 2023

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. First, private cloud infrastructure providers like Amazon (AWS), Microsoft (Azure), and Google (GCP) began by offering more cost-effective and elastic resources for fast access to infrastructure.

Data Quality 52

Data Quality Cloud Data Data Pipeline Data Observability 52

IBM Journey to AI blog

SEPTEMBER 11, 2023

Don Haderle, a retired IBM Fellow and considered to be the “father of Db2,” viewed 1988 as a seminal point in its development as D B2 version 2 proved it was viable for online transactional processing (OLTP)—the lifeblood of business computing at the time. Db2 (LUW) was born in 1993, and 2023 marks its 30th anniversary.

Database 101

Database SQL Data Warehouse Machine Learning 101

IBM Journey to AI blog

JULY 17, 2023

AMC Networks is excited by the opportunity to capitalize on the value of all of their data to improve viewer experiences. “Watsonx.data could allow us to easily access and analyze our expansive, distributed data to help extract actionable insights.” ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks.

AI 74

AI AI Machine Learning Machine Learning 74

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

Women in Big Data

DECEMBER 9, 2024

Introduction In the rapidly evolving landscape of data analytics, Business Intelligence (BI) tools have become indispensable for organizations seeking to leverage their big data stores for strategic decision-making. Compared to Power BI or Tableau, it has fewer pre-built connectors outside the Google Cloud ecosystem.

Big Data 52

Big Data Big Data Power BI Tableau 52

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Microsoft Power BI has been the leader in the analytics and business intelligence platforms category for several years running.

Power BI 84

Power BI Analytics Analytics Azure 84

Alation

APRIL 7, 2021

Powered by the industry’s broadest and deepest connectivity, the Alation Data Catalog supports data intelligence use cases across an organization’s de facto hybrid cloud environments. Alation’s cloud offering delivers these same benefits, now available as a service. Alation Cloud Service is available on AWS.

Data Governance 52

Data Governance AWS Data Silos Data Lakes 52

Tableau

DECEMBER 7, 2022

As the world’s first real-time CRM, Salesforce Customer 360 and Data Cloud provide your entire organization with a single, up-to-the-minute view of your customer across any cloud. These features cover functionality for enterprise customer data in five key categories: Connect, Harmonize, Unify, Analyze and Predict, and Act.

Tableau 55

Tableau Data Warehouse Data Pipeline Data Visualization 55

The MLOps Blog

MAY 17, 2023

A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse. Further processes or workflows can then easily utilize this data to create business intelligence and analytics solutions. Operation ETL pipeline runs on schedule e.g. daily, weekly or monthly.

ETL 59

ETL Data Pipeline ML ML 59

Dataversity

MARCH 29, 2021

It has taken a global pandemic for organizations to finally realize that the old way of doing businesses – and the legacy technologies and processes that came with it – are no longer going to cut it. The post The Move to Public Cloud and an Intelligent Data Strategy appeared first on DATAVERSITY. As […].

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DataOps Data Lakes Azure AWS 94

phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

Data Science Blog

MAY 15, 2023

Data Lakehouse Architecture Eine kurze Geschichte des Data Lakehouse Das Konzept des Data Lakehouse ist relativ neu und entstand Mitte der 2010er Jahre als Reaktion auf die Einschränkungen des traditionellen Data Warehousing und die wachsende Beliebtheit von Data Lakes. So basieren z.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Data Science Blog

SEPTEMBER 3, 2024

Dabei arbeiten wir technologie-offen und mit nahezu allen Tools – Und oft in enger Verbindung mit Initiativen der Business Intelligence und Data Science. in Databricks oder den KI-Tools von Google, AWS und Mircosoft Azure (Azure Cognitive Services, Azure Machine Learning etc.).

Data Science 130

Data Science Power BI Azure Data Warehouse 130

Pickl AI

JANUARY 21, 2025

Summary: This blog delves into the various types of data warehouses, including Enterprise Data Warehouses, Operational Data Stores, Data Marts, Cloud Data Warehouses, and Big Data Warehouses. Each type serves distinct purposes and plays a crucial role in effective data management and analysis.

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