IBM Journey to AI blog

OCTOBER 30, 2023

Businesses globally recognize the power of generative AI and are eager to harness data and AI for unmatched growth, sustainable operations, streamlining and pioneering innovation. In this quest, IBM and AWS have forged a strategic alliance, aiming to transition AI’s business potential from mere talk to tangible action.

AWS 95

AWS Data Warehouse AI AI 95

Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. Read Many of the preferred platforms for analytics fall into one of these two categories.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

IBM Journey to AI blog

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. Let’s delve into the database portfolio from IBM available on AWS. 

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AWS Database ETL AI 93

AWS Machine Learning Blog

JUNE 5, 2023

This means that business analysts who want to extract insights from the large volumes of data in their data warehouse must frequently use data stored in Parquet. Canvas provides connectors to AWS data sources such as Amazon Simple Storage Service (Amazon S3), Athena, and Amazon Redshift. Choose Grant.

Machine Learning 96

Machine Learning Machine Learning AWS Data Lakes 96

IBM Journey to AI blog

MAY 9, 2023

Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 92

Data Warehouse AWS AI AI 92

Dataconomy

SEPTEMBER 4, 2023

A well-documented case is the UK government’s failed attempt to create a unified healthcare records system, which wasted billions of taxpayer dollars. Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Loading The transformed data is loaded into the target destination, such as a data warehouse.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Analytics Vidhya

OCTOBER 25, 2023

Introduction Struggling with expanding a business database due to storage, management, and data accessibility issues? To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023.

Database 220

Database Analytics Analytics Data Warehouse 220

Pickl AI

OCTOBER 15, 2024

ETL (Extract, Transform, Load) is a core process in data integration that involves extracting data from various sources, transforming it into a usable format, and loading it into a target system, such as a data warehouse. It supports both batch and real-time data processing , making it highly versatile.

ETL 52

ETL Azure AWS Data Governance 52

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. Best Practice 5.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

phData

APRIL 29, 2024

Understanding Fivetran Fivetran is a popular Software-as-a-Service platform that enables users to automate the movement of data and ETL processes across diverse sources to a target destination. The phData team achieved a major milestone by successfully setting up a secure end-to-end data pipeline for a substantial healthcare enterprise.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

phData

AUGUST 9, 2024

Typically, this data is scattered across Excel files on business users’ desktops. They usually operate outside any data governance structure; often, no documentation exists outside the user’s mind. Cloud Storage Upload Snowflake can easily upload files from cloud storage (AWS S3, Azure Storage, GCP Cloud Storage).

ETL 52

ETL Data Warehouse Data Governance Tableau 52

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

The MLOps Blog

MARCH 15, 2023

AWS provides several tools to create and manage ML model deployments. 2 If you are somewhat familiar with AWS ML base tools, the first thing that comes to mind is “Sagemaker”. AWS Sagemeaker is in fact a great tool for machine learning operations (MLOps) to automate and standardize processes across the ML lifecycle. S3 buckets.

AWS 52

AWS ETL ML ML 52

Alation

MARCH 1, 2022

Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

Precisely

MAY 13, 2024

Whether it’s a cloud data warehouse or a mainframe, look for vendors who have a wide range of capabilities that can adapt to your changing needs. It synthesizes all the metadata around your organization’s data assets and arranges the information into a simple, easy-to-understand format.

Data Governance 52

Data Governance Data Pipeline Cloud Data Data Quality 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. SageMaker Unified Studio provides a unified experience for using data, analytics, and AI capabilities. The table metadata is managed by Data Catalog.

SQL 139

SQL Data Analyst Data Warehouse AWS 139

Alation

FEBRUARY 8, 2022

Making the experts responsible for service streamlines the data-request pipeline, delivering higher quality data into the hands of those who need it more rapidly. Some argue that data governance and quality practices may vary between domains. Interoperable and governed by global standards. This is changing.

Data Governance 52

Data Governance Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Learn more about the cloud.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

JULY 25, 2023

Their primary responsibilities include: Data Storage and Management Data Engineers design and implement storage solutions for different types of data, be it structured, semi-structured, or unstructured. They work with databases and data warehouses to ensure data integrity and security.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Women in Big Data

DECEMBER 9, 2024

Its costs are associated with its enterprise-focused features and advanced data modeling capabilities. Lookers value is significant for organizations with complex data needs and a focus on data governance. Qlik Sense – Qlik is an industry leader in data integration and analytics solutions that support AI strategies.

Big Data 52

Big Data Big Data Power BI Tableau 52

phData

AUGUST 4, 2023

The external stage area includes Microsoft Azure Blob storage, Amazon AWS S3, and Google Cloud Storage. Amazon S3 for AWS, Azure Blob Storage for Azure, or Google Cloud Storage for GCP) to store the actual data files in micro-partitions. Cloud Storage Snowflake leverages the cloud’s native object storage services (e.g.

Database 52

Database Azure SQL AWS 52

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Data Science Blog

SEPTEMBER 3, 2024

Prinzipielle Architektur-Darstellung eines Data Lakehouse Systems unter Einsatz von Databricks auf der Goolge / Amazon / Microsoft Azure Cloud nach dem Data Mesh Konzept zur Bereitstellung von Data Products für Process Mining, BI und Data Science Applikationen. Dies sollte im Einzelfall geprüft werden.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

databricks

JUNE 16, 2025

Enterprises want to apply fine-grained access control policies to manage increasingly complex data governance requirements. Accepted Publications Accepted Industry Papers Databricks Lakeguard : Supporting fine-grained access control and multi-user capabilities for Apache Spark workloads.

Data Science 130

Data Science Artificial Intelligence Artificial Intelligence Business Intelligence 130