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

Alation

APRIL 12, 2022

CDOs have a mandate across the data value chain, across that whole life cycle of data. Data governance also extends across that life cycle. It’s not just about security or privacy or ensuring data quality; it’s also ensuring the right people can access it and use it to deliver value to the organization.”.

Data Quality 52

Data Quality Data Governance Data Silos Analytics 52

Precisely

JULY 15, 2024

Even without a specific architecture in mind, you’re building toward a framework that enables the right person to access the right data at the right time. However, complex architectures and data silos make that difficult. It’s time to rethink how you manage data to democratize it and make it more accessible.

Data Governance 72

Data Governance DataOps Data Silos Data Pipeline 72

Precisely

FEBRUARY 12, 2024

Before business users can tap into the value of their data to deliver positive outcomes, that data must be complete, contextual, timely, accurate, and available. In other words, the data needs to be freed from its silos. Data scientists spend most of their time combining, harmonizing, and validating disparate data sets.

Data Governance 64

Data Governance Analytics Analytics Machine Learning 64

Pickl AI

OCTOBER 6, 2024

This phase is crucial for enhancing data quality and preparing it for analysis. Transformation involves various activities that help convert raw data into a format suitable for reporting and analytics. Normalisation: Standardising data formats and structures, ensuring consistency across various data sources.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

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 93

AWS Database ETL AI 93

Pickl AI

DECEMBER 4, 2023

Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence. Think of data governance as the rules and regulations governing the kingdom of information. It ensures data quality , integrity, and compliance.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

Pickl AI

APRIL 14, 2023

With the exponential growth of data and increasing complexities of the ecosystem, organizations face the challenge of ensuring data security and compliance with regulations. Although Data Governance is not mandatory, it works with data quality and Master Data Management Tools.

Data Governance 52

Data Governance Data Quality Analytics Analytics 52

The MLOps Blog

MAY 17, 2023

ML heavily relies on ETL pipelines as the accuracy and effectiveness of a model are directly impacted by the quality of the training data. These pipelines assist data scientists in saving time and effort by ensuring that the data is clean, properly formatted, and ready for use in machine learning tasks.

ETL 59

ETL Data Pipeline ML ML 59

Pickl AI

NOVEMBER 15, 2023

Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible. Importance of Data Lakes Data Lakes play a pivotal role in modern data analytics, providing a platform for Data Scientists and analysts to extract valuable insights from diverse data sources.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Heartbeat

DECEMBER 7, 2023

What is Data Mesh? Data Mesh is a new data set that enables units or cross-functional teams to decentralize and manage their data domains while collaborating to maintain data quality and consistency across the organization — architecture and governance approach. We can call fabric texture or actual fabric.

Data Governance 52

Data Governance Deep Learning Deep Learning Artificial Intelligence 52

Pickl AI

JULY 16, 2024

Here’s what you need to consider: Data integration: Ensure your data from various IT systems (applications, networks, security tools) is integrated and readily accessible for AIOps tools to analyze. This might involve data cleansing and standardization efforts.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

MARCH 15, 2024

This is a guest blog post written by Nitin Kumar, a Lead Data Scientist at T and T Consulting Services, Inc. Duration of data informs on long-term variations and patterns in the dataset that would otherwise go undetected and lead to biased and ill-informed predictions. Much of this work comes down to the data.”

AWS 128

AWS ML ML Data Silos 128

phData

SEPTEMBER 27, 2024

Data Quality Management : Persistent staging provides a clear demarcation between raw and processed customer data. This makes it easier to implement and manage data quality processes, ensuring your marketing efforts are based on clean, reliable data. Nope, we’re now thinking in streams, baby!

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52