DataKitchen

FEBRUARY 17, 2025

Manually writing tests limits the scope of what gets tested and can introduce biases, making it difficult to get a complete picture of data quality. Organizations that fail to prioritize data quality testing risk compromising their data integrity, affecting their ability to make informed business decisions.

SQL 74

SQL Python Government Data Engineering 74

Teradata

MAY 30, 2025

Teradata Block File System (BFS) enhances data domain isolation by providing a high-performance, scalable storage solution that supports efficient data management and retrieval. This system ensures that data is stored in a structured manner, facilitating quick access and processing while maintaining data integrity and security.

AWS 52

AWS Architecture Building Amazon Web Services 52

Precisely

JULY 18, 2024

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

Data Management 52

Data Management Management Metadata Database-centric 52

Striim

APRIL 18, 2025

If data is delayed, outdated, or missing key details, leaders may act on the wrong assumptions. Regulatory Compliance Demands Data Governance: Data privacy laws such as GDPR and CCPA require organizations to track, secure, and audit sensitive information. Start Your Free Trial | Schedule a Demo

High Quality Data 52

High Quality Data Business Intelligence Unstructured Data Data Pipeline 52

Ascend.io

OCTOBER 28, 2024

It is important to note that normalization often overlaps with the data cleaning process, as it helps to ensure consistency in data formats, particularly when dealing with different sources or inconsistent units. Data Validation Data validation ensures that the data meets specific criteria before processing.

Raw Data 52

Raw Data Aggregated Data Data Pipeline Data Validation 52

Precisely

MAY 31, 2023

To innovate, compete, and grow in the current macroeconomic environment, enterprises must approach data strategically. A sound data strategy doesn’t happen by accident; it’s built on a foundation of data integrity , including accuracy, consistency, and rich context. Many organizations still struggle with data integrity.

Data Integration 52

Data Integration Metadata Data Governance Government 52

Precisely

MAY 3, 2023

Learn more The countdown is on to Trust ’23: the Precisely Data Integrity Summit! We recently announced the details of our annual virtual event , and we’re thrilled to once again bring together thousands of data professionals worldwide for two days of knowledge, insights, and inspiration for your data integrity journey.

Data Integration 52

Data Integration Government Data Governance AWS 52

AltexSoft

OCTOBER 8, 2021

The good news is, businesses can choose the path of data integration to make the most out of the available information. The bad news is, integrating data can become a tedious task, especially when done manually. Data integration in a nutshell. Data integration process. That’s a lot of work.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

JUNE 6, 2025

It enables consistent reads and writes, even in highly concurrent environments, making it a go-to choice for modern data lake architectures. To understand why Apache Iceberg is gaining widespread attention to simplify data management, it’s essential to look at the powerful capabilities that set it apart from traditional formats.

Architecture 40

Architecture Data Lake Metadata Cloud Storage 40

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Precisely

JULY 15, 2024

Key Takeaways Data Mesh is a modern data management architectural strategy that decentralizes development of trusted data products to support real-time business decisions and analytics. However, complex architectures and data silos make that difficult. One strategy being leveraged is a data mesh.

Data Governance 72

Data Governance Government Data Integration Data 72

Monte Carlo

JUNE 16, 2023

Data integrity and quality may seem similar at first glance, and they are sometimes used interchangeably in everyday life, but they play unique roles in successful data management. You can have data quality, without data integrity.

Data Integration 52

Data Integration Hospitality Banking Healthcare 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. See it in action and schedule a demo with one of our data experts today.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. See it in action and schedule a demo with one of our data experts today.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. See it in action and schedule a demo with one of our data experts today.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

APRIL 7, 2023

Like technical debt, data debt represents the liability accrued over time by inefficient and outdated methods and technologies for handling corporate data. It is important to note that data debt has methodological and technological components. Data management technologies grow old and out of date.

Management 98

Management Government Data Technology 98

The Modern Data Company

JULY 24, 2023

This integration allows for a comprehensive understanding of relationships and patterns within the data, leading to more accurate and insightful analysis. Chaining data products opens a world of possibilities for organizations seeking to maximize the value of their data assets.

Data Lake 85

Data Lake Transportation Data Algorithm 85

The Modern Data Company

FEBRUARY 2, 2024

This efficiency doesn’t just speed things up; it fundamentally changes how swiftly and effectively you can harness the power of your data assets. This approach doesn’t just solve existing problems; it paves the way for a new era of efficiency and effectiveness in data management.

Raw Data 75

Raw Data Government Utilities Data 75

AltexSoft

SEPTEMBER 10, 2021

To get a single unified view of all information, companies opt for data integration. In this article, you will learn what data integration is in general, key approaches and strategies to integrate siloed data, tools to consider, and more. What is data integration and why is it important?

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

The Modern Data Company

APRIL 20, 2023

On the surface, it’s an operating system designed specifically for managing and processing large amounts of data. It typically provides a scalable and flexible infrastructure for storing, processing, and analyzing big data and should also include features that support data management, data protection, and data governance.

Systems 95

Systems Entertainment Government Big Data 95

Cloudera

APRIL 15, 2019

Cloudera Flow Management (CFM) is a no-code data ingestion and management solution powered by Apache NiFi. With a slick user interface, 300+ processors and the NiFi Registry, CFM delivers highly scalable data management and DevOps capabilities to the enterprise. Cloudera Flow Management.

Management 17

Management Data Ingestion Data Collection Government 17

The Modern Data Company

JULY 18, 2023

High-quality data, free from errors, inconsistencies, or biases, forms the foundation for accurate analysis and reliable insights. Data products should incorporate mechanisms for data validation, cleansing, and ongoing monitoring to maintain data integrity. Request a demo today and see it in action.

Data Governance 69

Data Governance High Quality Data Government Data 69

Cloudera

JUNE 25, 2019

Cloudera shared a comprehensive overview and demonstration of the all-new Cloudera Data Platform (CDP). This industry-first enterprise data cloud offering will include cloud-native services for data warehousing, machine learning, streaming ingest, and operational data stores.

Cloud 87

Cloud Entertainment Government Machine Learning 87

Monte Carlo

JULY 22, 2024

Data doesn’t just flow – it floods in at breakneck speed. How do we track this tsunami of changes, ensure data integrity, and extract meaningful insights? Data versioning is the answer. Data versioning is the practice of tracking and managing changes to datasets over time.

Metadata 52

Metadata Datasets ETL Tools Data 52

Striim

AUGUST 20, 2024

Striim facilitates this transformation by enabling the implementation of a data mesh and supporting the migration to Google Cloud. The data mesh approach decentralizes data management, making it easier for various teams across an organization to perform self-service analytics and derive actionable insights.

Retail 52

Retail Cloud Google Cloud Data Architecture 52

ProjectPro

JUNE 6, 2025

CRN editorial team, has appreciated this challenge taken up by various big data companies and identified the best big data and business analytics companies that are innovating out-of-the-box data management, business analytics and infrastructure services and technologies in the big data market.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

The Modern Data Company

JULY 24, 2023

This integration allows for a comprehensive understanding of relationships and patterns within the data, leading to more accurate and insightful analysis. Chaining data products opens a world of possibilities for organizations seeking to maximize the value of their data assets.

Data Lake 52

Data Lake Transportation Data Algorithm 52

The Modern Data Company

JULY 24, 2023

This integration allows for a comprehensive understanding of relationships and patterns within the data, leading to more accurate and insightful analysis. Chaining data products opens a world of possibilities for organizations seeking to maximize the value of their data assets.

Data Lake 52

Data Lake Transportation Data Algorithm 52

The Modern Data Company

JULY 18, 2023

High-quality data, free from errors, inconsistencies, or biases, forms the foundation for accurate analysis and reliable insights. Data products should incorporate mechanisms for data validation, cleansing, and ongoing monitoring to maintain data integrity. Request a demo today and see it in action.

Data Governance 52

Data Governance High Quality Data Government Data 52

The Modern Data Company

JULY 18, 2023

High-quality data, free from errors, inconsistencies, or biases, forms the foundation for accurate analysis and reliable insights. Data products should incorporate mechanisms for data validation, cleansing, and ongoing monitoring to maintain data integrity. Request a demo today and see it in action.

Data Governance 52

Data Governance High Quality Data Government Data 52

Cloudera

AUGUST 31, 2021

The Accenture Smart Data Transition Toolkit is also tightly integrated with Cloudera Data Platform for cloud data management and Cloudera Shared Data Experiences for secure, self-service analytics. To learn more about CDP & the Smart Data Transition Toolkit: . Demo Video. Value Achieved.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Cloudera

MAY 9, 2019

Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data. It is meant for you to assess if you have thought through processes such as continuous data ingestion, enterprise data integration and data governance.

Manufacturing 56

Manufacturing Data Ingestion Architecture Data Governance 56

Precisely

MAY 2, 2024

When it comes to customer-related transactions and analytics, your data’s integrity, accuracy, and accessibility directly impact your business’s ability to operate efficiently and deliver value to customers. That’s what makes slow, manual customer data management so damaging. The solution?

Coding Skills 69

Coding Skills Food Data Process 69

Workfall

JULY 25, 2023

In this blog, we’ll demonstrate step-by-step the process of reading and writing data in Google Sheets, empowering you to effortlessly manage your data with the power of Python. Say goodbye to time-consuming tasks and hello to streamlined data integration – let’s get started! Why Sheety?

Python 76

Python Programming Language Coding Project 76

Striim

SEPTEMBER 11, 2024

Are we going to be using intermediate data stores to store data as it flows to the destination? Are we collecting data from the origin in predefined batches or in real time? Step 4: Design the data processing plan Once data is ingested, it must be processed and transformed for it to be valuable to downstream systems.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98