Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Dataversity

FEBRUARY 1, 2021

In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […].

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Dataversity

JANUARY 11, 2021

In Part 1 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […].

Data Warehouse 59

Data Warehouse Business Intelligence Business Intelligence Data Profiling 59

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

Pickl AI

MARCH 3, 2025

Summary: Business Intelligence Analysts transform raw data into actionable insights. They use tools and techniques to analyse data, create reports, and support strategic decisions. Key skills include SQL, data visualization, and business acumen. Introduction We are living in an era defined by data.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

IBM Journey to AI blog

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

Pickl AI

JANUARY 28, 2025

Summary: Understanding Business Intelligence Architecture is essential for organizations seeking to harness data effectively. This framework includes components like data sources, integration, storage, analysis, visualization, and information delivery. What is Business Intelligence Architecture?

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 26, 2025

These stages ensure that data flows smoothly from its source to its final destination, typically a data warehouse or a business intelligence tool. By facilitating a systematic approach to data management, ETL pipelines enhance the ability of organizations to analyze and leverage their data effectively.

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ETL Data Pipeline Business Intelligence Business Intelligence 91

IBM Journey to AI blog

OCTOBER 2, 2024

Business intelligence (BI) users often struggle to access the high-quality, relevant data necessary to inform strategic decision making. Inconsistent data quality: The uncertainty surrounding the accuracy, consistency and reliability of data pulled from various sources can lead to risks in analysis and reporting.

Business Intelligence 58

Business Intelligence Business Intelligence Power BI Data Quality 58

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. What is ETL? Let’s break down each step: 1.

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ETL Data Quality Data Warehouse Analytics 105

DagsHub

AUGUST 23, 2024

As such, the quality of their data can make or break the success of the company. This article will guide you through the concept of a data quality framework, its essential components, and how to implement it effectively within your organization. What is a data quality framework?

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Dataconomy

MAY 26, 2025

Understanding the data-driven philosophy Organizations excelling in business analytics view data as a vital asset and strive to leverage it for strategic competitive advantages. How business analytics works Business analytics involves several foundational processes that guide organizations in their analytical endeavors.

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

IBM Journey to AI blog

OCTOBER 22, 2024

The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it. Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

AWS Machine Learning Blog

APRIL 3, 2025

Embracing generative AI with Amazon Bedrock The company has identified several use cases where generative AI can significantly impact operations, particularly in analytics and business intelligence (BI). This tool democratizes data access across the organization, enabling even nontechnical users to gain valuable insights.

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AWS Data Governance Data Silos SQL 86

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. Understand what insights you need to gain from your data to drive business growth and strategy.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Pickl AI

MARCH 19, 2025

It helps data engineers collect, store, and process streams of records in a fault-tolerant way, making it crucial for building reliable data pipelines. Amazon Redshift Amazon Redshift is a cloud-based data warehouse that enables fast query execution for large datasets.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. You can review the recommendations and augment rules from over 25 included data quality rules.

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AWS ML ML Data Quality 96

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Data Warehouse 98

Data Warehouse Azure SQL ETL 98

ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Database 130

Database Data Visualization Big Data Big Data 130

ODSC - Open Data Science

APRIL 25, 2025

Unfortunately, the current landscape of our consuming systems, especially business intelligence tools, just wont work withAPIs. They offer the ability to specify a schema, expected values, and even such things as data quality expectations. These specifications are kept close to the code and versioned with it.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

APRIL 9, 2025

By 2025, global data volumes are expected to reach 181 zettabytes, according to IDC. To harness this data effectively, businesses rely on ETL (Extract, Transform, Load) tools to extract, transform, and load data into centralized systems like data warehouses. What are ETL Tools?

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ETL Data Warehouse AWS Business Intelligence 52

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Introduction In today’s data-driven landscape, organisations are increasingly reliant on Data Analytics to inform decision-making and drive business strategies.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

phData

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

IBM Journey to AI blog

DECEMBER 7, 2023

Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses. They are seamlessly integrated with cloud-based data warehouses, facilitating the collection, storage and analysis of data from various sources.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

Alation

JULY 19, 2022

Finally, a data catalog can help data scientists find answers to their questions (and avoid re-asking questions that have already been answered). Modern data catalogs surface a wide range of data asset types. Modern data catalogs also facilitate data quality checks.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Ensuring data quality is made easier as a result.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Assess Data Quality.

Data Quality 52

Data Quality Data Warehouse Data Profiling Data Governance 52

Flipboard

MAY 9, 2025

This pattern creates a comprehensive solution that transforms raw social media data into actionable business intelligence (BI) through advanced AI capabilities. 3B Instruct Amazon Bedrock, the system provides tailored marketing content that adds business value. By integrating LLMs such as Anthropics Claude 3.5

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AWS Natural Language Processing AI AI 97

Pickl AI

AUGUST 9, 2024

Real-world examples illustrate their application, while tools and technologies facilitate effective hierarchical data management in various industries. Data Quality Issues Inconsistent or incomplete data can hinder the effectiveness of hierarchies. What Are Common Challenges When Implementing Hierarchies?

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming. Two problems arise.

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

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

Alation

FEBRUARY 7, 2023

It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a data warehouse project. Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company. What’s the right lineage level?

Data Warehouse 52

Data Warehouse ETL Business Intelligence Business Intelligence 52