Business Intelligence, Data Silos and SQL

Business Intelligence

Data Silos

SQL

IBM to help businesses scale AI workloads, for all data, anywhere

IBM Journey to AI blog

MAY 9, 2023

Supporting the data management life cycle According to IDC’s Global StorageSphere, enterprise data stored in data centers will grow at a compound annual growth rate of 30% between 2021-2026. [2] ” Notably, watsonx.data runs both on-premises and across multicloud environments. .

Data Warehouse

Data Warehouse AWS AI AI

Exploring the fundamentals of online transaction processing databases

Dataconomy

APRIL 27, 2023

They are also designed to handle concurrent access by multiple users and applications, while ensuring data integrity and transactional consistency. Examples of OLTP databases include Oracle Database, Microsoft SQL Server, and MySQL. OLAP systems support business intelligence, data mining, and other decision support applications.

Database

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Connecting Amazon Redshift and RStudio on Amazon SageMaker

AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

AWS

AWS Machine Learning Machine Learning Database

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Maximizing Profit and Productivity: The New Era of AI-Powered Accounting

Automation, Evolved: Your New Playbook For Smarter Knowledge Work

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Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Pickl AI

NOVEMBER 15, 2023

This centralization streamlines data access, facilitating more efficient analysis and reducing the challenges associated with siloed information. With all data in one place, businesses can break down data silos and gain holistic insights. It often serves as a source for Data Warehouses.

Data Lakes

Data Lakes Data Warehouse Database ETL

Data architecture strategy for data quality

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality

Data Quality Data Lakes Data Warehouse Big Data

AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. Trusted, governed data is essential for ensuring the accuracy, relevance and precision of AI.

AI AI Data Quality Database

Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS

AWS Database ETL AI

How to Build a Successful Metadata Management Framework

Alation

JUNE 28, 2022

With a metadata management framework, your data analysts: Optimize search and findability: Create a single portal using role-based access for rapid data access based on job function and need. Establish business glossaries: Define business terms and create standard relationships for data governance.

Data Governance

Data Governance Data Analyst Machine Learning Machine Learning

Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

SEPTEMBER 29, 2023

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

Data Lakes

Data Lakes Clustering Big Data Big Data

Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes

Data Lakes Data Warehouse Azure Apache Hadoop

Data Intelligence empowers informed decisions

Pickl AI

DECEMBER 4, 2023

Marketing Targeted Campaigns Increases campaign effectiveness and ROI Data silos leading to inconsistent information. Implementing integrated data management systems. 6,20000 Analytical skills, proficiency in Data Analysis tools (e.g., 9,43,649 Business acumen, Data Visualisation tools (e.g.,

Data Analysis

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence

Simplify data access for your enterprise using Amazon SageMaker Lakehouse

Flipboard

DECEMBER 4, 2024

Currently, organizations often create custom solutions to connect these systems, but they want a more unified approach that them to choose the best tools while providing a streamlined experience for their data teams. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

Data Lakes

Data Lakes Data Warehouse AWS Database

Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

APRIL 3, 2025

By analyzing their data, organizations can identify patterns in sales cycles, optimize inventory management, or help tailor products or services to meet customer needs more effectively. One key initiative is ODAPChat, an AI-powered chat-based assistant employees can use to interact with data using natural language queries.

AWS

AWS Data Governance Data Silos SQL

dbt Labs’ Coalesce 2023 Recap

phData

NOVEMBER 13, 2023

Enhanced Collaboration: dbt Mesh fosters a collaborative environment by using cross-project references, making it easy for teams to share, reference, and build upon each other’s work, eliminating the risk of data silos. Tableau (beta) Google Sheets (beta) Hex Klipfolio PowerMetrics Lightdash Mode Push.ai

Database

Database Business Intelligence Business Intelligence Data Silos

Data Science Current

IBM to help businesses scale AI workloads, for all data, anywhere

Exploring the fundamentals of online transaction processing databases

Webinars

Trending Sources

Connecting Amazon Redshift and RStudio on Amazon SageMaker

Webinars

Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Data architecture strategy for data quality

AI that’s ready for business starts with data that’s ready for AI

Tackling AI’s data challenges with IBM databases on AWS

How to Build a Successful Metadata Management Framework

Drowning in Data? A Data Lake May Be Your Lifesaver

Data platform trinity: Competitive or complementary?

Data Intelligence empowers informed decisions

Simplify data access for your enterprise using Amazon SageMaker Lakehouse

Shaping the future: OMRON’s data-driven journey with AWS

dbt Labs’ Coalesce 2023 Recap

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