IBM Journey to AI blog

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Data Warehouse 58

Data Warehouse Data Engineering Data Engineer Data Engineering 58

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Loading The transformed data is loaded into the target destination, such as a data warehouse.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Alation

APRIL 14, 2022

This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. The Cloud Data Migration Challenge. Data pipeline orchestration. Cloud governance.

Data Governance 59

Data Governance ML ML Cloud Data 59

IBM Journey to AI blog

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. As data grows exponentially, so do the complexities of managing and leveraging it to fuel AI and analytics. Increase metadata maturity.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

AWS Machine Learning Blog

JUNE 5, 2023

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet due to its compact and highly efficient format. In this post, we show you how to import Parquet data to Canvas from Athena, where Lake Formation enables data governance.

Machine Learning 83

Machine Learning Machine Learning AWS Data Lakes 83

Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

Data Governance 64

Data Governance ML ML Augmented Analytics 64

Pickl AI

OCTOBER 19, 2023

Regular Data Audits Conduct regular data audits to identify issues and discrepancies. This proactive approach allows you to detect and address problems before they compromise data quality. Data Governance Framework Implement a robust data governance framework.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. What Is the Role of the Cloud in Data Modernization? How to Modernize Data with Alation.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

phData

JULY 18, 2023

Why Migrate to a Modern Data Stack? 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. Data teams can focus on delivering higher-value data tasks with better organizational visibility.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

IBM Journey to AI blog

MARCH 14, 2024

Try Db2 Warehouse SaaS on AWS for free   Netezza SaaS on AWS IBM® Netezza® Performance Server is a cloud-native data warehouse designed to operationalize deep analytics, data mining and BI by unifying, accessing and scaling all types of data across the hybrid cloud. Netezza

AWS 93

AWS Database ETL AI 93

IBM Journey to AI blog

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

DagsHub

AUGUST 23, 2024

As companies increasingly rely on data for decision-making, poor-quality data can lead to disastrous outcomes. Even the most sophisticated ML models, neural networks, or large language models require high-quality data to learn meaningful patterns. When bad data is inputted, it inevitably leads to poor outcomes.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 3, 2024

Multiple data applications and formats make it harder for organizations to access, govern, manage and use all their data for AI effectively. Scaling data and AI with technology, people and processes Enabling data as a differentiator for AI requires a balance of technology, people and processes.

AI 45

AI AI Data Quality Database 45

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).

Database 52

Database Analytics Analytics Machine Learning 52

The MLOps Blog

MARCH 15, 2023

This includes the tools and techniques we used to streamline the ML model development and deployment processes, as well as the measures taken to monitor and maintain models in a production environment. Costs: Oftentimes, cost is the most important aspect of any ML model deployment. This includes data quality, privacy, and compliance.

AWS 52

AWS ETL ML ML 52

phData

APRIL 18, 2023

Snowflake enables organizations to instantaneously scale to meet SLAs with timely delivery of regulatory obligations like SEC Filings, MiFID II, Dodd-Frank, FRTB, or Basel III—all with a single copy of data enabled by data sharing capabilities across various internal departments.

Data Silos 52

Data Silos ETL Clustering Analytics 52

Alation

JANUARY 25, 2022

This is a key component of active data governance. These capabilities are also key for a robust data fabric. Another key nuance of a data fabric is that it captures social metadata. Social metadata captures the associations that people create with the data they produce and consume. The Power of Social Metadata.

DataOps 52

DataOps SQL ML ML 52

Alation

APRIL 14, 2023

Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys. People were familiar with the value of a data catalog (and the growing need for data governance ), though many admitted to being somewhat behind on their journeys.

Data Pipeline 52

Data Pipeline Data Warehouse Cloud Data ETL 52

phData

SEPTEMBER 27, 2024

Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. Building a composable CDP requires some serious data engineering chops.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52