ODSC - Open Data Science

SEPTEMBER 27, 2023

Storage Optimization: Data warehouses use columnar storage formats and indexing to enhance query performance and data compression. They excel at managing structured data and supporting ACID (Atomicity, Consistency, Isolation, Durability) transactions.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

Pickl AI

JULY 18, 2023

SAS: Analytics and Business Intelligence SAS is a leading programming language for analytics and business intelligence. It provides a comprehensive suite of tools for data manipulation, statistical analysis, and predictive modeling. It offers tools for data exploration, ad-hoc querying, and interactive reporting.

Data Science 52

Data Science Data Scientist Python Business Intelligence 52

ODSC - Open Data Science

JUNE 12, 2023

Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. The Power BI Datamarts support sensitivity labels, endorsement, discovery, and Row-Level Security ( RLS ), which help protect and manage the data according to the business requirements and compliance needs.

ETL 52

ETL Business Intelligence Data Science Data Analysis 52

IBM Journey to AI blog

DECEMBER 16, 2022

The solution also helps with data quality management by assigning data quality scores to assets and simplifies curation with AI-driven data quality rules.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

Mlearning.ai

AUGUST 10, 2023

The project I did to land my business intelligence internship — CAR BRAND SEARCH ETL PROCESS WITH PYTHON, POSTGRESQL & POWER BI 1. It is a data integration process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target system.

Business Intelligence 52

Business Intelligence ETL Data Analysis Python 52

AWS Machine Learning Blog

SEPTEMBER 6, 2023

As an Information Technology Leader, Jay specializes in artificial intelligence, data integration, business intelligence, and user interface domains.

Generative AI 98

Generative AI Large Language Models AI AI 98

Pragnakalp

JUNE 8, 2023

Introduction : Microsoft Fabric is a cloud-based platform that offers a unified data science, data engineering, and business intelligence experience. It provides a variety of features and services, such as data preparation, machine learning, and visualization.

Data Science 52

Data Science Machine Learning Business Intelligence NLP 52

Pickl AI

AUGUST 1, 2023

Data Transformation: Converting, cleaning, and enriching raw data into a structured and consistent format suitable for analysis and reporting. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Big Data 52

Big Data Data Analysis Data Scientist Data Ingestion 52

AWS Machine Learning Blog

SEPTEMBER 28, 2023

As an Information Technology Leader, Jay specializes in artificial intelligence, data integration, business intelligence, and user interface domains. In this role, he functions as the Global Generative AI Lead Architect and also the Lead Architect for Supply Chain Solutions with AABG.

Generative AI 99

Generative AI Large Language Models Artificial Intelligence Artificial Intelligence 99

Pickl AI

APRIL 26, 2024

During a data analysis project, I encountered a significant data discrepancy that threatened the accuracy of our analysis. I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Unite.AI

DECEMBER 5, 2023

This article will explore data warehousing, its architecture types, key components, benefits, and challenges. What is Data Warehousing? Data warehousing is a data management system to support Business Intelligence (BI) operations. It can handle vast amounts of data and facilitate complex queries.

Metadata 162

Metadata Big Data ETL Data Ingestion 162

Marktechpost

JULY 18, 2023

ETL solutions employ several data management strategies to automate the extraction, transformation, and loading (ETL) process, reducing errors and speeding up data integration. Skyvia Skyvia is a cloud data platform created by Devart that enables no-coding data integration, backup, management, and access.

ETL 52

ETL Data Integration Automation Business Intelligence 52

IBM Journey to AI blog

NOVEMBER 14, 2023

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. But few organizations have made the strategic shift to managing “data as a product.”

ESG 302

ESG Generative AI AI AI 302

Marktechpost

JULY 23, 2023

A data warehouse is a data management system for data reporting, analysis, and storage. It is an enterprise data warehouse and is part of business intelligence. Data from one or more diverse sources is stored in data warehouses, which are central repositories. Integrate.io Integrate.io

Machine Learning 52

Machine Learning ETL Big Data Data Integration 52

Pickl AI

NOVEMBER 15, 2023

On the other hand, a Data Warehouse is a structured storage system designed for efficient querying and analysis. It involves the extraction, transformation, and loading (ETL) process to organize data for business intelligence purposes. It often serves as a source for Data Warehouses.

ETL 52

ETL Business Intelligence Metadata Data Analysis 52

IBM Journey to AI blog

OCTOBER 12, 2023

Security and privacy —When all data scientists and AI models are given access to data through a single point of entry, data integrity and security are improved. They can also spot and root out bias and drift proactively by monitoring, cataloging and governing their models.

Data Scientist 221

Data Scientist Metadata Responsible AI Explainability 221

ODSC - Open Data Science

JANUARY 30, 2024

Not only does it involve the process of collecting, storing, and processing data so that it can be used for analysis and decision-making, but these professionals are responsible for building and maintaining the infrastructure that makes this possible; and so much more.

Data Science 52

Data Science Data Mining Data Scientist Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

Data Ingestion 113

Data Ingestion Metadata NLP Data Scientist 113

IBM Journey to AI blog

OCTOBER 20, 2023

AI technology is quickly proving to be a critical component of business intelligence within organizations across industries. Store operating platform : Scalable and secure foundation supports AI at the edge and data integration. trillion in value.

Machine Learning 213

Machine Learning Automation AI AI 213

Artificial Corner

JUNE 6, 2023

This period also saw the development of the first data warehouses, large storage repositories that held data from different sources in a consistent format. The concept of data warehousing was introduced by Bill Inmon, often referred to as the “father of data warehousing.” Morgan Kaufmann. Dean, J., & Ghemawat, S.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Pickl AI

JULY 12, 2023

Besides, it allows users to filter and sort data, perform calculations, and create simple visualizations. While Excel is not as powerful as specialized data manipulation tools, it is widely accessible and user-friendly.

Data Analysis 52

Data Analysis Data Quality Data Science Python 52

Marktechpost

JULY 17, 2023

TIBCO Statistica With several collaboration and workflow capabilities included in the product to enable business intelligence throughout a company, TIBCO strongly emphasizes usability. This makes it a wise decision for your business if you anticipate using the tool by less experienced workers.

Machine Learning 98

Machine Learning Data Mining Data Scientist Artificial Intelligence 98

The MLOps Blog

MAY 17, 2023

Significance of ETL pipeline in machine learning The significance of ETL pipelines lies in the fact that they enable organizations to derive valuable insights from large and complex data sets. Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines.

ETL 59

ETL ML Machine Learning Data Scientist 59

IBM Journey to AI blog

AUGUST 4, 2023

Here are some advantages—and potential risk—to consider during this organizational change: Productivity Many companies look to data democratization to eliminate silos and get more out of their data across departments. Security Data security is a high priority.

Machine Learning 173

Machine Learning AI AI Automation 173