Precisely

JANUARY 17, 2023

Technology helped to bridge the gap, as AI, machine learning, and data analytics drove smarter decisions, and automation paved the way for greater efficiency. Data integrity trends for 2023 promise to be an important year for all aspects of data management. Read The Corinium report to learn more.

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Precisely

OCTOBER 23, 2023

When most people think of master data management, they first think of customers and products. But master data encompasses so much more than data about customers and products. Challenges of Master Data Management A decade ago, master data management (MDM) was a much simpler proposition than it is today.

Data Management 110

Data Management Management Data Data Integration 110

The Modern Data Company

JANUARY 22, 2024

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. In response, The Modern Data Company emerged, driven by a clear mission: to revolutionize data management and address challenges posed by a diverse and rapidly evolving data environment.

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Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. AI drives the demand for data integrity.

Data Analytics 72

Data Analytics Data Governance Data Integration Government 72

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

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. There are a number of projects and platforms on the market that target data integration.

Data Integration 100

Data Integration Coding BI Data Engineering 100

The Modern Data Company

JANUARY 22, 2024

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. In response, The Modern Data Company emerged, driven by a clear mission: to revolutionize data management and address challenges posed by a diverse and rapidly evolving data environment.

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Data Engineering Podcast

JULY 13, 2020

Summary The first stage of every data pipeline is extracting the information from source systems. There are a number of platforms for managing data integration, but there is a notable lack of a robust and easy to use open source option. If you hand a book to a new data engineer, what wisdom would you add to it?

Data Integration 100

Data Integration Data Engineering Data Engineer Data 100

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

Data Engineering Podcast

AUGUST 27, 2021

Summary The reason that so much time and energy is spent on data integration is because of how our applications are designed. By making the software be the owner of the data that it generates, we have to go through the trouble of extracting the information to then be used elsewhere. What is Zero-Copy Integration?

Data Integration 100

Data Integration Architecture Data Warehouse Data Lake 100

Data Engineering Podcast

NOVEMBER 20, 2021

Summary One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. With the improvements in streaming engines it is now possible to perform all of your data integration in near real time, but it can be challenging to understand the proper processing patterns to make that performant.

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Data Lake Data Integration Lambda Architecture Process 100

Data Engineering Podcast

JANUARY 25, 2021

In this episode they describe the data integration challenges facing many B2B companies, how their work on the Hotglue platform simplifies their efforts, and how they have designed the platform to make these ETL workloads embeddable and self service for end users. Can you start by describing what you are building at Hotglue?

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Data Integration IT Python BI 100

Data Engineering Podcast

MAY 1, 2022

Summary The predominant pattern for data integration in the cloud has become extract, load, and then transform or ELT. Contact Info LinkedIn Matillion Contact Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Visit [link] to learn more.

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Data Warehouse Data Integration Cloud Google Cloud 100

Precisely

JANUARY 9, 2023

Requirements for data to be more easily accessible, at even faster rates, will continue to grow in 2023, and organizations will need to adapt their data quality practices to keep pace with the demand for new modern use cases. The post Top Data Integrity Trends Fueling Confident Business Decisions in 2023 appeared first on Precisely.

Data Integration 81

Data Integration Data Governance Government Data 81

Data Engineering Podcast

JULY 2, 2021

Summary Data integration in the form of extract and load is the critical first step of every data project. There are a large number of commercial and open source projects that offer that capability but it is still far from being a solved problem. Can you start by describing what the Singer ecosystem is?

Data Integration 100

Data Integration SQL BI Data Warehouse 100

Data Engineering Podcast

JANUARY 23, 2022

In this episode Abhi Sivasailam shares his experience designing and implementing a data mesh solution with his team at Flexport, and the importance of defining and enforcing data contracts that are implemented at those domain boundaries. Can you start by explaining what your working definition of a "data contract" is?

Data Integration 100

Data Integration Data Pipeline Data Architecture 100

Precisely

SEPTEMBER 18, 2024

This means it’s more important than ever to make data-driven decisions, cut costs, and improve efficiency. Get your copy of the full report for all the strategic insights you need to build a winning data strategy in 2025. Data quality is the top data integrity challenge for 64% of organizations this year, up from 50% last year.

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Data Integration Data Governance Government Data Programming 72

Precisely

DECEMBER 14, 2023

Data integrity empowers your businesses to make fast, confident decisions based on trusted data that has maximum accuracy, consistency, and context. As 2023 comes to an end we’re counting down the Top 5 Data Integrity blog posts of the year. #5. Read more > #2.

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Data Integration AWS Machine Learning Data 69

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.

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Data Integration Metadata Telecommunication Data Governance 64

Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. AI drives the demand for data integrity.

Data Analytics 59

Data Analytics Data Governance Government Data Integration 59

Precisely

DECEMBER 9, 2024

Top reported benefits of data governance programs include improved quality of data analytics and insights (58%), improved data quality (58%), and increased collaboration (57%). Data governance is a top data integrity challenge, cited by 54% of organizations second only to data quality (56%).

Data Governance 64

Data Governance Government Data Integration Architecture 64

Data Engineering Podcast

APRIL 10, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Data Integration 100

Data Integration Data Engineering Data Engineer SQL 100

Data Engineering Podcast

JULY 3, 2022

In this episode they explain how the utility is implemented to run quickly and how you can start using it in your own data workflows to ensure that your data warehouse isn’t missing any records from your source systems. Can you describe what the data diff tool is and the story behind it?

Data Integration 100

Data Integration MongoDB MySQL Scala 100

Precisely

AUGUST 8, 2024

As your business applications grow, so do fragmented data silos that hold you back. How confident are you that your data management practices are up to the task of supporting your evolving objectives? MDM: The Answer to Data Chaos Imagine managing a sprawling organization where each department operates with its own datasets.

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Data Integration Data Management Data Datasets 52

Precisely

MARCH 7, 2024

However, that is rarely the case, falling far short of true data integrity that delivers accuracy, consistency, and context. As part of a holistic data integrity approach, companies implement data governance programs to build trust in the data.

Data Integration 59

Data Integration Building Data Governance Government 59

Hevo

MAY 11, 2023

A few problems one might have to deal with while trying to expand their Database are storage problems, complicated management issues, and difficulty in the location, sharing, and checking of isolated data. One of the biggest stumbling blocks of a business is the expansion of its Database.

Data Management 89

Data Management Management Database Data 89

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.

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Data Management Management Metadata Database-centric 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

Precisely

OCTOBER 31, 2024

Key Takeaways: Data mesh is a decentralized approach to data management, designed to shift creation and ownership of data products to domain-specific teams. Data fabric is a unified approach to data management, creating a consistent way to manage, access, and share data across distributed environments.

Data Architecture 69

Data Architecture Architecture Metadata Government 69

Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Data Engineering Podcast

MAY 21, 2023

Summary Batch vs. streaming is a long running debate in the world of data integration and transformation. In this episode David Yaffe and Johnny Graettinger share the story behind the business and technology and how you can start using it today to build a real-time data lake without all of the headache.

Data Lake 162

Data Lake Machine Learning Kafka Data Warehouse 162

Striim

JUNE 18, 2024

In today’s fast-paced world, staying ahead of the competition requires making decisions informed by the freshest data available — and quickly. That’s where real-time data integration comes into play. What is Real-Time Data Integration + Why is it Important? Why is Real-Time Data Integration Important?

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Data Integration Data Lake Retail Healthcare 52

Precisely

MARCH 18, 2025

If attendees learn from the shared experiences offered by Gartner and many of the customer speakers and practitioners, theyll be better equipped to drive greater value from their organizations data strategies. Familiar recommendations included: Tie your data strategy and priorities to clear and measurable business value.

Data Analytics 64

Data Analytics Data Governance Government Consulting 64

Data Engineering Podcast

FEBRUARY 26, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management 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. We feel your pain.

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Building Machine Learning Metadata Data Integration 147

Data Engineering Podcast

MARCH 5, 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.

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Building Machine Learning Database Design Metadata 147

Snowflake

NOVEMBER 19, 2024

Spark clusters needed manual maintenance to avoid waste and took 10-15 minutes to spin up, while the managed Spark platform outside Snowflake raised data governance concerns, impacting data integrity and security.

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Data Governance Government Healthcare Building 98

Ascend.io

DECEMBER 4, 2024

Further Exloration: What is data automation? Deploy DataOps DataOps , or Data Operations, is an approach that applies the principles of DevOps to data management. It aims to streamline and automate data workflows, enhance collaboration and improve the agility of data teams.

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Data Pipeline Metadata Data Workflow Data 52