The Data Administration Newsletter

OCTOBER 17, 2023

Where exactly within an organization does the primary responsibility lie for ensuring that a data pipeline project generates data of high quality, and who exactly holds that responsibility? Who is accountable for ensuring that the data is accurate? Is it the data engineers? The data scientists?

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Data Pipeline Data Quality Data Governance Data Analyst 52

Dataversity

NOVEMBER 15, 2023

Those who want to design universal data pipelines and ETL testing tools face a tough challenge because of the vastness and variety of technologies: Each data pipeline platform embodies a unique philosophy, architectural design, and set of operations.

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Data Pipeline ETL Data Governance Data Quality 59

IBM Journey to AI blog

AUGUST 23, 2023

Because of this, when we look to manage and govern the deployment of AI models, we must first focus on governing the data that the AI models are trained on. This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. and watsonx.data.

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Data Governance AI AI Artificial Intelligence 66

AWS Machine Learning Blog

APRIL 3, 2025

Data governance challenges Maintaining consistent data governance across different systems is crucial but complex. The company aims to integrate additional data sources, including other mission-critical systems, into ODAP. The following diagram shows a basic layout of how the solution works.

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AWS Data Governance Data Silos SQL 80

Precisely

AUGUST 29, 2024

Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability continuously monitors data pipelines and alerts you to errors and anomalies. stored: where is it located?

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Data Governance Data Quality Data Observability AI 52

Dataversity

MAY 26, 2023

Suppose you’re in charge of maintaining a large set of data pipelines from cloud storage or streaming data into a data warehouse. How can you ensure that your data meets expectations after every transformation? That’s where data quality testing comes in.

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Data Pipeline Data Warehouse Data Quality Data Observability 52

Dataversity

JUNE 19, 2023

In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline.

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Data Pipeline Database Data Modeling Data Models 52

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program?

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Data Governance Data Quality Data Analyst Data Pipeline 52

Alation

FEBRUARY 20, 2020

The rise of data lakes, IOT analytics, and big data pipelines has introduced a new world of fast, big data. How Data Catalogs Can Help. Data catalogs evolved as a key component of the data governance revolution by creating a bridge between the new world and old world of data governance.

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Data Governance Tableau Analytics Analytics 52

IBM Data Science in Practice

NOVEMBER 28, 2022

Implementing a data fabric architecture is the answer. What is a data fabric? Data fabric is defined by IBM as “an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems.”

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ODSC - Open Data Science

JANUARY 9, 2024

This will become more important as the volume of this data grows in scale. Data Governance Data governance is the process of managing data to ensure its quality, accuracy, and security. Data governance is becoming increasingly important as organizations become more reliant on data.

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Data Engineering Data Engineer Data Engineering Data Engineering 97

Alation

MAY 31, 2023

The Data Governance & Information Quality Conference (DGIQ) is happening soon — and we’ll be onsite in San Diego from June 5-9. If you’re not familiar with DGIQ, it’s the world’s most comprehensive event dedicated to, you guessed it, data governance and information quality. The best part?

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Data Governance DataOps Data Pipeline Business Intelligence 52

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. These data requirements could be satisfied with a strong data governance strategy.

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Data Governance Data Engineering Data Engineering Data Engineer 52

Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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Data Pipeline Data Governance Data Lakes Data Warehouse 40

Dataversity

JUNE 26, 2023

The same expectation applies to data, […] The post Leveraging Data Pipelines to Meet the Needs of the Business: Why the Speed of Data Matters appeared first on DATAVERSITY. Today, businesses and individuals expect instant access to information and swift delivery of services.

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Dataconomy

FEBRUARY 12, 2024

This shift leverages the capabilities of modern data warehouses, enabling faster data ingestion and reducing the complexities associated with traditional transformation-heavy ETL processes. These platforms provide a unified view of data, enabling businesses to derive insights from diverse datasets efficiently. Image credit ) 5.

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ETL Data Governance Machine Learning Machine Learning 195

Dataversity

MARCH 13, 2023

Companies are spending a lot of money on data and analytics capabilities, creating more and more data products for people inside and outside the company. These products rely on a tangle of data pipelines, each a choreography of software executions transporting data from one place to another.

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Data Observability Data Pipeline Analytics Analytics 98

IBM Journey to AI blog

FEBRUARY 26, 2024

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. That’s why data pipeline observability is so important.

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Data Pipeline Data Engineering Data Engineering Data Engineer 112

Precisely

JANUARY 9, 2023

It enables business users to proactively address potential problems as they happen, resulting in healthier data pipelines, more productive teams, and happier customers. Many businesses now cite faster access to relevant data, and higher quality of data and insights, as being the top benefits of data governance initiatives.

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Data Governance Data Quality Data Observability Data Pipeline 81

IBM Journey to AI blog

APRIL 10, 2023

To further the above, organizations should have the right foundation that consists of a modern data governance approach and data architecture. It’s becoming critical that organizations should adopt a data architecture that supports AI governance.

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AI AI Data Governance Data Pipeline 103

Smart Data Collective

OCTOBER 17, 2022

A potential option is to use an ELT system — extract, load, and transform — to interact with the data on an as-needed basis. It may conflict with your data governance policy (more on that below), but it may be valuable in establishing a broader view of the data and directing you toward better data sets for your main models.

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Big Data Big Data Data Engineering Data Engineering 119

Dataconomy

FEBRUARY 23, 2023

This involves creating data validation rules, monitoring data quality, and implementing processes to correct any errors that are identified. Creating data pipelines and workflows Data engineers create data pipelines and workflows that enable data to be collected, processed, and analyzed efficiently.

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Big Data Big Data Data Engineering Data Engineer 91

Pickl AI

OCTOBER 11, 2023

What is Data Observability? It is the practice of monitoring, tracking, and ensuring data quality, reliability, and performance as it moves through an organization’s data pipelines and systems. Data quality tools help maintain high data quality standards. Tools Used in Data Observability?

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Data Observability Data Quality Data Pipeline Data Governance 52

Pickl AI

NOVEMBER 4, 2024

Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? They are crucial in ensuring data is readily available for analysis and reporting. from 2025 to 2030.

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Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

OCTOBER 10, 2023

In today’s fast-paced business environment, the significance of Data Observability cannot be overstated. Data Observability enables organizations to detect anomalies, troubleshoot issues, and maintain data pipelines effectively. How Are Data Quality and Data Observability Similar—and How Are They Different?

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Data Observability Data Quality Data Governance Data Pipeline 52

Precisely

SEPTEMBER 30, 2024

Data enrichment adds context to existing information, enabling business leaders to draw valuable new insights that would otherwise not have been possible. Managing an increasingly complex array of data sources requires a disciplined approach to integration, API management, and data security.

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Data Quality Data Governance Machine Learning Machine Learning 52

Alation

FEBRUARY 20, 2020

Alation’s deep integration with tools like MicroStrategy and Tableau provides visibility into the complete data pipeline: from storage through visualization. Get the latest data cataloging news and trends in your inbox. In creating a single source of truth, MicroStrategy has reduced the risk of error or misinterpretation.

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Data Governance Tableau Hadoop Data Pipeline 52

Alation

FEBRUARY 20, 2020

We believe that this offering, Alation Tableau Edition, realizes the full promise of self-service analytics by allowing analysts to self-serve without making any of the errors of omission or commission that traditionally accompany an ungoverned data environment. We characterize this offering as Governance for Insight.

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Tableau Data Governance Data Pipeline Analytics 52

Alation

SEPTEMBER 22, 2022

This new partnership will unify governed, quality data into a single view, granting all stakeholders total visibility into pipelines and providing them with a superior ability to make data-driven decisions. For people to understand and trust data, they need to see it in context. Data Pipeline Strategy.

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Data Pipeline Data Quality Data Governance Data Engineering 52

IBM Journey to AI blog

APRIL 20, 2023

This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change? Moreover, banks must stay in compliance with industry regulations like BCBS 239, which focus on improving banks’ risk data aggregation and risk reporting capabilities.

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Database Data Engineering Data Engineering Data Engineer 86

IBM Journey to AI blog

OCTOBER 12, 2023

Securing AI models and their access to data While AI models need flexibility to access data across a hybrid infrastructure, they also need safeguarding from tampering (unintentional or otherwise) and, especially, protected access to data. And that makes sense.

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AI AI Data Scientist Data Governance 93

Precisely

JULY 15, 2024

Watch Preparing for a Data Mesh Strategy Key pillars when preparing for a data mesh strategy include: A mature data governance strategy to manage and organize a decentralized data system. Proper governance ensures that data is uniformly accessible and the appropriate security measures are met.

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phData

APRIL 23, 2024

Designing New Data Pipelines Takes a Considerable Amount of Time and Knowledge Designing new ingestion pipelines is a complex undertaking that demands significant time and expertise. Engineering teams must maintain a complex web of ingestion pipelines capable of supporting many different sources, each with its own intricacies.

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Tableau

OCTOBER 8, 2021

Connecting directly to this semantic layer will help give customers access to critical business data in a safe, governed manner. This partnership makes data more accessible and trusted. Our continued investments in connectivity with Google technologies help ensure your data is secure, governed, and scalable.

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IBM Journey to AI blog

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions provide new clients with affordable and high impact capabilities to expeditiously explore and validate the path to become a data-driven enterprise. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture.

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Data Governance Data Science AI AI 58

Alation

DECEMBER 23, 2021

The best data was discovered, experts were identified, and conversations were starting. For the first time, data governance was no longer a naughty concept. Yup, the big syndicate was doing data culture – nice data culture. Now, elves of all rank and file can: Know their data and how they can use it.

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Data Governance Data Pipeline Tableau Big Data 59

Alation

DECEMBER 7, 2021

Do we have end-to-end data pipeline control? What can we learn about our data quality issues? How can we improve and deliver trusted data to the organization? One major obstacle presented to data quality is data silos , as they obstruct transparency and make collaboration tough. Unified Teams.

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