Pickl AI

JUNE 28, 2023

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. Data integration is a vital component of successful data mining initiatives.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

phData

MAY 13, 2024

Difficulty in moving non-SAP data into SAP for analytics which encourages data silos and shadow IT practices as business users search for ways to extract the data (which has data governance implications). Additionally, change data markers are not available for many of these tables.

Database 52

Database Analytics Analytics Machine Learning 52

IBM Journey to AI blog

JANUARY 5, 2023

Critical capabilities of modern high-quality data quality management solutions require an organization to: Enforce data governance across an organization by augmenting manual data quality processes with metadata and AI-related technologies. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

DrivenData Labs

MARCH 30, 2023

PETs Prize Challenges was to advance privacy-preserving federated learning solutions that provide end-to-end privacy and security protections while harnessing the potential of AI for overcoming significant global challenges. Shaishav Jain is a Data Science Associate Consultant at ZS.

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

Mlearning.ai

SEPTEMBER 4, 2023

Short-termism: AI budgets are increasing, but much of that spending is taken from other business areas. This downward pressure forces AI projects to be less exploratory, less patient (e.g., Do Foundation Model Providers Comply with the EU AI Act?” overlooking safety, security, compliance, and governance), and hastier.

AI 52

AI AI Azure Machine Learning 52

IBM Journey to AI blog

SEPTEMBER 5, 2024

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

phData

AUGUST 11, 2023

Data engineering in healthcare is taking a giant leap forward with rapid industrial development. Artificial Intelligence (AI) and Machine Learning (ML) are buzzwords these days with developments of Chat-GPT, Bard, and Bing AI, among others. Through big data models, hospitals can identify trends that guide smart decision-making.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Heartbeat

DECEMBER 7, 2023

Data should be designed to be easily accessed, discovered, and consumed by other teams or users without requiring significant support or intervention from the team that created it. Data should be created using standardized data models, definitions, and quality requirements. How does it? Keep following my future content.

Data Governance 52

Data Governance Deep Learning Deep Learning Artificial Intelligence 52

Pickl AI

SEPTEMBER 12, 2024

Introduction Machine Learning has evolved significantly, from basic algorithms to advanced models that drive today’s AI innovations. A key advancement is Federated Learning, which enhances privacy and efficiency by training models across decentralised devices.

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52

Pickl AI

DECEMBER 4, 2023

Imagine this: we collect loads of data, right? Data Intelligence takes that data, adds a touch of AI and Machine Learning magic, and turns it into insights. It’s not just about having data; it’s about turning that data into real wisdom for better products and services. These insights?

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

IBM Journey to AI blog

OCTOBER 30, 2023

A successful public health response to a future pandemic will rely on collecting and managing critical data, investing in smart, capable and flexible data modernization systems, and preparing people with the proper knowledge and skills. Lesson 1: Use a data model built for public health.

Data Modeling 78

Data Modeling Data Models Data Silos Machine Learning 78