IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing.

Analytics 118

Analytics Data-driven Data Integration Data Lake 118

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

SEPTEMBER 13, 2024

To share data to our internal consumers, we use AWS Lake Formation with LF-Tags to streamline the process of managing access rights across the organization. Data integration workflow A typical data integration process consists of ingestion, analysis, and production phases.

Interactive 110

Interactive Strategy Cost-Benefit Data Governance 110

AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. This connector provides comprehensive access to SFTP storage, facilitating cloud ETL processes for operational reporting, backup and disaster recovery, data governance, and more.

Data Processing 114

Data Processing Visualization Data Lake Data Processing 114

erwin

MARCH 26, 2020

In the whitepaper he states, the priority of the citizen analyst is straightforward: find the right data to develop reports and analyses that support a larger business case. Increased data variety, balancing structured, semi-structured and unstructured data, as well as data originating from a widening array of external sources.

Data-driven 90

Data-driven Unstructured Data Enterprise Machine Learning 90

Smarten

AUGUST 4, 2023

If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization. Machine learning capability determines the best techniques, and the best fit transformations for data so that the outcome is clear and concise.

Data Lake 52

Data Lake Machine Learning Data Integration Data Quality 52

Octopai

JUNE 9, 2024

During audits, HealthCo could clearly show how data was handled and processed, reducing the risk of non-compliance penalties. This not only protected the organization legally but also reinforced its commitment to high standards of data governance.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

AWS Big Data

JULY 25, 2023

About Talend Talend is an AWS ISV Partner with the Amazon Redshift Ready Product designation and AWS Competencies in both Data and Analytics and Migration. Talend Cloud combines data integration, data integrity, and data governance in a single, unified platform that makes it easy to collect, transform, clean, govern, and share your data.

Data Analytics 52

Data Analytics Analytics Data Warehouse Data Processing 52

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

FineReport

JUNE 7, 2024

Elevate your data transformation journey with Dataiku’s comprehensive suite of solutions. Key Features Intuitive Data Visualization Tools : Tableau offers a wide range of intuitive tools that allow users to create interactive data visualization effortlessly.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

Alation

AUGUST 11, 2022

Everybody’s trying to solve this same problem (of leveraging mountains of data), but they’re going about it in slightly different ways. Data fabric is a technology architecture. It’s a data integration pattern that brings together different systems, with the metadata, knowledge graphs, and a semantic layer on top.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Smarten

JANUARY 4, 2018

Think of your data warehouse as an active repository that is ever changing as new data sources keep on getting added and existing data sources keep on getting updated. In order to manage the environment, an organization must dedicate resources to monitor and track ETL process, its data flow, data integration and data updates.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

Jet Global

MAY 21, 2025

Unlocking the full potential of your data is about more than just visualizing it. True data transformation comes from applying insights to make impactful business decisions. Maintains data governance, ensuring accuracy and compliance. Encourages greater exploration and understanding of data.

Dashboards 59

Dashboards Visualization Reporting Interactive 59

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

MARCH 14, 2024

Jet streamlines many aspects of data administration, greatly improving data solutions built on Microsoft Fabric. It enhances analytics capabilities, streamlines migration, and enhances data integration. Through Jet’s integration with Fabric, your organization can better handle, process, and use your data.

Analytics 52

Analytics Management Reporting Data Quality 52

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting. With Atlas, you can put your data security concerns to rest.

Reporting 52

Reporting Finance Data Quality Sales 52

Wayne Yaddow

MARCH 28, 2025

First: It is critical to set up a thorough data inventory and assessment procedure. Organizations must do a comprehensive inventory of their current data repositories, recording the data sources, kind, structure, and quality before starting data integration.

Data Quality 52

Data Quality Data Integration Data Governance Metadata 52

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Testing 130

Testing Data Quality Data Governance Data-driven 130

CIO Business Intelligence

JANUARY 24, 2024

Gather/Insert data on market trends, customer behavior, inventory levels, or operational efficiency. IoT, Web Scraping, API, IDP, RPA Data Processing Data Pipelines and Analysis Layer Employ data pipelines with algorithms to filter, sort, and interpret data, transforming raw information into actionable insights.

IoT 118

IoT Machine Learning Internet of Things Optimization 118