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 Data 52

Knowledge Hut

APRIL 20, 2023

Data governance refers to the set of policies, procedures, mix of people and standards that organisations put in place to manage their data assets. It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

Precisely

SEPTEMBER 8, 2023

In the meantime, data quality and overall data integrity suffer from neglect. According to a recent report on data integrity trends from Drexel University’s LeBow College of Business , 41% reported that data governance was a top priority for their data programs.

Data Governance 52

Data Governance Government Data Big Data 52

Data Engineering Podcast

FEBRUARY 22, 2021

Summary Data integration is a critical piece of every data pipeline, yet it is still far from being a solved problem. There are a number of managed platforms available, but the list of options for an open source system that supports a large variety of sources and destinations is still embarrasingly short.

Data Integration 100

Data Integration Data Warehouse Data Pipeline BI 100

Precisely

JANUARY 5, 2023

For some companies that do have a formal strategy, that strategy may be little more than a technical exercise, the primary purpose of which is to lay out the nuts and bolts of data management, compliance, and similar baseline requirements. Data governance plays a critical role in any effective data strategy.

Data Governance 52

Data Governance Government Data Raw Data 52

Precisely

JUNE 26, 2023

They shore up privacy and security, embrace distributed workforce management, and innovate around artificial intelligence and machine learning-based automation. The key to success within all of these initiatives is high-integrity data. Typically, businesses generate data in siloed applications.

Data Integration 52

Data Integration Data Cleanse Data Governance Data Programming 52

Data Engineering Podcast

NOVEMBER 30, 2020

Summary The first stage of every good pipeline is to perform data integration. With the increasing pace of change and the need for up to date analytics the need to integrate that data in near real time is growing. Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud.

Data Integration 100

Data Integration Coding BI Kafka 100

Databand.ai

JUNE 21, 2023

Eric Jones June 21, 2023 What Are Data Integrity Tools? Data integrity tools are software applications or systems designed to ensure the accuracy, consistency, and reliability of data stored in databases, spreadsheets, or other data storage systems. In this article: Why Are Data Integrity Tools Important?

Data Integration 52

Data Integration Data Cleanse Data Validation Telecommunication 52

Precisely

JULY 19, 2023

Data governance is fast becoming a business imperative. Many top executives and line-of-business managers lack a clear understanding of the benefits of data governance. Data governance plays a critical role in risk management and compliance as well. How can you within your organization?

Data Governance 52

Data Governance Government Building Data 52

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

Data Engineering Podcast

OCTOBER 5, 2020

Summary Analytical workloads require a well engineered and well maintained data integration process to ensure that your information is reliable and up to date. Building a real-time pipeline for your data lakes and data warehouses is a non-trivial effort, requiring a substantial investment of time and energy.

Data Integration 100

Data Integration Kafka Data Lake Machine Learning 100

Precisely

MARCH 14, 2023

Deploy, execute, and scale natively in modern cloud architectures To meet the need for data quality in the cloud head on, we’ve developed the Precisely Data Integrity Suite. The modules of the Data Integrity Suite seamlessly interoperate with one another to continuously build accuracy, consistency, and context in your data.

Data Integration 52

Data Integration High Quality Data BI Data 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 Data Lake Management 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 Data Lake Management 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 Data Lake Management Data Warehouse 52

Databand.ai

JUNE 20, 2023

Niv Sluzki June 20, 2023 What Is Data Integrity? Data integrity refers to the overall accuracy, consistency, and reliability of data stored in a database, data warehouse, or any other information storage system.

Data Integration 52

Data Integration Data Validation Pharmaceutical Data Cleanse 52

The Modern Data Company

APRIL 15, 2024

Understands how different pieces of data (books) relate to each other, helping users find related information. Keeps the library orderly, adjusting as new data arrives. Tracks key performance indicators to understand the use and value of the data. Manages information about data access and monitors data quality.

Government 52

Government Metadata Data Data Lake 52

Precisely

AUGUST 3, 2023

The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. Let’s explore more of the report’s findings around data program successes, challenges, influences, and more.

Data Integration 98

Data Integration Data Programming Programming Data 98

Databand.ai

MAY 30, 2023

Data quality can be influenced by various factors, such as data collection methods, data entry processes, data storage, and data integration. Maintaining high data quality is crucial for organizations to gain valuable insights, make informed decisions, and achieve their goals.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Precisely

MAY 18, 2023

The annual Precisely Data Integrity Summit , Trust ’23, was another amazing success that virtually brought together thousands of data professionals worldwide. Here’s a recap of what Precisely customers had to say about their data integrity successes, and what they’ve discovered along the way.

Data Governance 52

Data Governance Insurance Government Data Integration 52

Precisely

FEBRUARY 23, 2024

How Industry Leaders Get Superior Results The majority of respondents in the Arizent/Digital Insurance study rated their data management processes as being only moderately effective at meeting the core criteria for success. Data quality is just one very important element of data integrity.

Insurance 64

Insurance Data Validation Government High Quality Data 64

ProjectPro

FEBRUARY 16, 2023

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. Data integration with ETL has changed in the last three decades. Q) Does AWS have an ETL Tool?

AWS 52

AWS Data Management ETL Tools Management 52

Data Engineering Podcast

FEBRUARY 19, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Hey there podcast listener, are you tired of dealing with the headache that is the 'Modern Data Stack'? It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze.

IT 147

IT Data Lake Metadata Data Warehouse 147

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 Utilities Government Data 75

Precisely

JANUARY 6, 2023

Environmental, social, and governance (ESG) initiatives are topics of discussion everywhere – in the workplace, social media, news outlets, and beyond. Recent public advocacy efforts around climate issues, diversity and inclusion, data privacy, and more have been driving forces in pushing ESG to the forefront. And for good reason.

Government 52

Government Education Data Integration Media 52

Databand.ai

AUGUST 30, 2023

Besides these categories, specialized solutions tailored specifically for particular domains or use cases also exist, such as ETL (Extract-Transform-Load) tools for managing data pipelines, data integration tools for combining information from disparate sources/systems, and more.

Data Cleanse 52

Data Cleanse Data Validation Data Pipeline Datasets 52

Knowledge Hut

MARCH 28, 2024

Data Engineer Career: Overview Currently, with the enormous growth in the volume, variety, and veracity of data generated and the will of large firms to store and analyze their data, data management is a critical aspect of data science. That’s where data engineers are on the go.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Data Management 42

Data Management Management Metadata Government 42

Precisely

SEPTEMBER 11, 2023

At Precisely, we recognize the value and potential of AI to help our customers work faster and smarter, and make more powerful, confident decisions grounded in trusted data – supporting our overall mission of unlocking data integrity for organizations of all kinds.

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

ThoughtSpot

MARCH 5, 2024

While AI-powered, self-service BI platforms like ThoughtSpot can fully operationalize insights at scale by delivering visual data exploration and discovery, it still requires robust underlying data management. Snowflake's new dynamic tables feature redefines how BI and analytics teams approach data transformation pipelines.

BI 94

BI Datasets Raw Data SQL 94

Snowflake

NOVEMBER 14, 2023

In a recent Snowflake in Healthcare 2023 report, KLAS evaluated the Snowflake Healthcare & Life Sciences Data Cloud based on its data integration, cloud capabilities and performance across six customer experience pillars: culture, loyalty, operations, product, relationship and value. Manager, Aug. Director, Sep.

Healthcare 82

Healthcare Data Warehouse Data Governance Cloud 82

Precisely

JUNE 6, 2023

As the scale and scope of data continue to increase, that creates new challenges with respect to compliance, governance, and data quality. To create more value from data, organizations must take a very proactive approach to data integrity. She also emphasizes the need to automate as much as possible.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Data Cleanse 65

Data Cleanse Data Governance Unstructured Data Cloud Storage 65

Databand.ai

AUGUST 30, 2023

This includes defining roles and responsibilities related to managing datasets and setting guidelines for metadata management. Risk mitigation and compliance management: Ensuring your organization’s adherence to industry regulations becomes easier with trustworthy datasets.

Building 52

Building Data Cleanse Data Governance Datasets 52

Knowledge Hut

APRIL 23, 2024

With the advent of technology and the arrival of modern communications systems, computer science professionals worldwide realized big data size and value. As big data evolves and unravels more technology secrets, it might help users achieve ambitious targets. This is one of the disadvantages of big data in healthcare.

Big Data 52

Big Data Media Government Big Data Skills 52

Precisely

MAY 23, 2024

Key takeaways: Quickly adapt to market changes by easily adding new data sources and targets, ensuring your IT landscape evolves at the pace of your business. Gain a competitive edge with real-time data integration, crucial for time-sensitive decisions and actions in fraud detection and customer interactions.

Data Integration 52

Data Integration Metadata Telecommunication Data Governance 52