KDnuggets

JANUARY 19, 2023

In this article, we will discuss use cases and methods for using ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes along with SQL to integrate data from various sources.

ETL 308

ETL SQL Data Engineering Data Engineer 308

KDnuggets

APRIL 19, 2022

Let's take a look at what goes into creating a foundation for enterprise-wide data intelligence and how AI and ML can permanently transform data integration.

Artificial Intelligence 308

Artificial Intelligence Artificial Intelligence ML ML 308

KDnuggets

AUGUST 1, 2022

Extract-Transform-Load vs Extract-Load-Transform: Data integration methods used to transfer data from one source to a data warehouse. Their aims are similar, but see how they differ.

ETL 219

ETL Data Warehouse Data Science 219

KDnuggets

MAY 30, 2023

Looking to integrate ChatGPT into your data science workflow? Here’s an example along with tips and best practices to get the most out of ChatGPT for data science.

Data Science 196

Data Science 196

databricks

MAY 15, 2023

We recently announced our partnership with Databricks to bring multi-cloud data clean room collaboration capabilities to every Lakehouse. Our integration with Databricks combines.

Cloud Data 185

Cloud Data 185

insideBIGDATA

FEBRUARY 16, 2024

In this contributed article, April Miller, senior IT and cybersecurity writer for ReHack Magazine, believes that when professionals are aware their data sets have missing, incomplete or inaccurate values, cleaning is often their first instinct. While it is an adequate approach, it won’t result in the same benefits as proactive action.

Analytics 397

Analytics Analytics 397

Dataconomy

MAY 25, 2022

Preventing cloud data warehouse failure is possible through proper integration. Utilizing your data is key to success. The importance of using data to make.

Data Warehouse 201

Data Warehouse Cloud Data Data Science AI 201

Dataconomy

FEBRUARY 20, 2023

Data integration and business intelligence are two critical components of a modern data-driven organization. While both are essential to managing data and driving insights, they serve different purposes and have unique characteristics.

Business Intelligence 168

Business Intelligence Business Intelligence Analytics Analytics 168

KDnuggets

NOVEMBER 24, 2021

Maintaining a centralized data repository can simplify your business intelligence initiatives. Here are four data integration tools that can make data more valuable for modern enterprises.

Business Intelligence 196

Business Intelligence Business Intelligence Data Preparation Analytics 196

Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions.

Data Governance 52

Data Governance Data Pipeline Data Quality Cloud Data 52

Precisely

JANUARY 17, 2023

Technology helped to bridge the gap, as AI, machine learning, and data analytics drove smarter decisions, and automation paved the way for greater efficiency. Data integrity trends for 2023 promise to be an important year for all aspects of data management. Read The Corinium report to learn more.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

KDnuggets

AUGUST 19, 2019

What’s the best way to execute your data integration tasks: writing manual code or using ETL tool? Find out the approach that best fits your organization’s needs and the factors that influence it.

ETL 215

ETL Data Science 215

Precisely

MARCH 7, 2024

That, in a nutshell, is why data integrity is so important. You should view enterprise data integrity through the same lens. Precisely believes that “the whole truth” is essential to data integrity. 53% of respondents cited missing information as a critical challenge impacting data quality.

Data Quality 52

Data Quality Database Administration Data Governance Analytics 52

IBM Data Science in Practice

FEBRUARY 5, 2023

This article gives an overview of the code experience for data scientists in Watson Studio on Cloud Pak for Data 4.6. We cover the new improved VS Code Desktop integration, JupyterLab- and RStudio- integration. This enforces permissions and privacy rules defined in Cloud Pak for Data, like when using built-in tools.

Python 130

Python Clustering Data Scientist Data Science 130

Precisely

DECEMBER 14, 2023

Data integrity empowers your businesses to make fast, confident decisions based on trusted data that has maximum accuracy, consistency, and context. As 2023 comes to an end we’re counting down the Top 5 Data Integrity blog posts of the year. #5. Read more > #2.

AWS 69

AWS Artificial Intelligence Artificial Intelligence Machine Learning 69

IBM Journey to AI blog

MARCH 29, 2024

It may be the solution that finally breaks through dysfunctional silos of business units, applications, data and people, and moves beyond the constraints that have cost companies dearly. Challenge 1: Orchestrate relevant data The journey to generative AI begins with data management. And it’s not just a technology change.

AI 86

AI AI Artificial Intelligence Artificial Intelligence 86

Smart Data Collective

SEPTEMBER 4, 2023

Its core benefits include increased productivity, cost savings, and the ability to handle large volumes of data seamlessly. Think about the plethora of sensitive data processed daily: contracts, personal identification details, financial statements, and more. Regular data audits are also crucial. Backup your data, too.

Artificial Intelligence 101

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 101

Dataversity

APRIL 16, 2024

Data, particularly real-time data, is an essential asset. But it is only […] The post Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity appeared first on DATAVERSITY. Hospitals and surgery centers must be efficient in handling their resources.

Analytics 59

Analytics Analytics 59

Flipboard

JUNE 6, 2023

Cloudera got its start in the Big Data era and is now moving quickly into the era of Big AI with large language models (LLMs). Today, Cloudera announced its strategy and tools for helping enterprises integrate the power of LLMs and generative AI into the company’s Cloudera Data Platform (CDP). …

Big Data 109

Big Data Big Data AI AI 109

Smart Data Collective

OCTOBER 20, 2021

The data integration landscape is under a constant metamorphosis. In the current disruptive times, businesses depend heavily on information in real-time and data analysis techniques to make better business decisions, raising the bar for data integration. Why is Data Integration a Challenge for Enterprises?

ML 122

ML ML Big Data Big Data 122

Dataversity

AUGUST 16, 2023

The term “big data” is no longer the exclusive preserve of big companies. Businesses of all sizes increasingly see the benefits of being data-driven. Effective access to […] The post Building Resilient Data Ecosystems for Safeguarding Data Integrity and Security appeared first on DATAVERSITY.

Business Intelligence 80

Business Intelligence Business Intelligence Big Data Big Data 80

databricks

MARCH 13, 2024

Sharing a belief that open source solutions will foster innovation and transparency in generative AI development, Databricks has announced a partnership and participation.

AI 328

AI AI 328

ODSC - Open Data Science

APRIL 24, 2024

Data scientists only witness the green power of data analytics with smart integrations. There is publicly known potential, with more strategies yet to be discovered for how data can decarbonize and optimize for net-zero and circular targets. What about the water wasted cleaning production lines or failed lab tests?

Analytics 52

Analytics Analytics Data Scientist Data Science 52

Dataversity

NOVEMBER 7, 2022

Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality.

Data Observability 97

Data Observability Data Quality Data Governance 97

Precisely

MAY 31, 2023

To innovate, compete, and grow in the current macroeconomic environment, enterprises must approach data strategically. A sound data strategy doesn’t happen by accident; it’s built on a foundation of data integrity , including accuracy, consistency, and rich context. Many organizations still struggle with data integrity.

Data Quality 52

Data Quality Data Governance Data Observability ETL 52

databricks

MAY 9, 2023

As organizations are maturing their data infrastructure and accumulating more data than ever before in their data lakes, Open and Reliable table formats.

Data Lakes 222

Data Lakes Data Engineering Data Engineer Data Engineering 222

Precisely

JUNE 15, 2023

To generate meaningful business value, however, telecom companies must develop and sustain high levels of data integrity within their telecom data. Telecoms face a multitude of challenges as they strive to maintain trust in their data. Data quality, likewise, is a persistent problem for many telecom organizations.

Data Quality 52

Data Quality Analytics Analytics Machine Learning 52

databricks

JANUARY 10, 2024

Data engineers rely on math and statistics to coax insights out of complex, noisy data. Among the most important domains is calculus, which.

Data Engineering 202

Data Engineering Data Engineer Data Engineering Data Engineering 202

Flipboard

SEPTEMBER 2, 2023

This blog post is not the end of my journey to integrate GenAI with my “Thinking Like a Data Scientist” (TLADS) methodology, but it is the last post …

Data Scientist 105

Data Scientist Computer Science Computer Science Artificial Intelligence 105

Precisely

JULY 31, 2023

The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. Let’s explore more of the report’s findings around data integrity maturity, challenges, and priorities.

Data Quality 52

Data Quality Data Governance Analytics Analytics 52

Flipboard

AUGUST 6, 2023

It’s incredible how many organizations utilize Generative AI (GenAI) and Large Language Models (LLMs) to enhance their information assembly, integration, and application abilities. The potential uses of GenAI… Read More »Integrating GenAI into “Thinking Like a Data Scientist” Methodology – Part I

Data Scientist 102

Data Scientist AI AI Artificial Intelligence 102