Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

datapine

SEPTEMBER 29, 2022

This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Alation

OCTOBER 26, 2021

Building a Data Culture Within a Finance Department. Our finance users tell us that their first exposure to the Alation Data Catalog often comes soon after the launch of organization-wide data transformation efforts. After all, finance is one of the greatest consumers of data within a business.

Finance 52

Finance Data Transformation Enterprise Metrics 52

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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

TDAN

AUGUST 15, 2023

Nearly every data leader I talk to is in the midst of a data transformation. As businesses look for ways to increase sales, improve customer experience, and stay ahead of the competition, they are realizing that data is their competitive advantage and the key to achieving their goals. And it’s no surprise, really.

Data Transformation 52

Data Transformation Sales Metadata Data Governance 52

Octopai

NOVEMBER 23, 2020

In fact, the LIBOR transition program marks one of the largest data transformation obstacles ever seen in financial services. Building an inventory of what will be affected is a huge undertaking across all of the data, reports, and structures that must be accounted for. Automated Data Lineage for Your LIBOR Project.

Metadata 72

Metadata Enterprise Business Intelligence Data Governance 72

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

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

Octopai

JANUARY 19, 2021

This is done by visualizing the Azure Data Factory pipelines’ full column-level with source-to-target traceability through different data transformations at the most detailed level. Octopai can fully map the BI landscape and trace metadata movement in a mixed environment including complex multi-vendor landscapes.

Metadata 52

Metadata ROI Machine Learning Data Quality 52

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data. Comprehensive data security and data governance (i.e.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

Octopai

AUGUST 11, 2024

By reverse-engineering, parsing, and converting scripts, Octopai seamlessly connects all data points within and across organizational systems. While open-source tools such as Apache Atlas, Open Metadata, Egeria, Spline, and OpenLineage offer valuable capabilities, they come with their own sets of pros and cons.

Metadata 40

Metadata Visualization Data Quality Data Governance 40

Alation

AUGUST 11, 2022

We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

APRIL 19, 2023

We took this a step further by creating a blueprint to create smart recommendations by linking similar data products using graph technology and ML. In this post, we showed how an organization can augment a data catalog with additional metadata by using ML and Neptune with an automated process.

Technology 105

Technology Data-driven Machine Learning Sales 105

AWS Big Data

DECEMBER 21, 2023

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

Alation

MARCH 22, 2022

More specifically, IDF has been integrated with Alation at an API level; this means that all generated pipeline code, metadata attributes, configuration files, and lineage are automatically synced (representing a huge time savings). They can better understand data transformations, checks, and normalization. Transparency is key.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 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. This is where Octopai excels.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

Ontotext

FEBRUARY 12, 2024

For many organizations, a centralized data platform will fall short as it gives data teams much less autonomy over managing increasingly diverse and voluminous datasets. It embraces the reality of business and specialized data needs within teams and organizations.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Alation

JANUARY 17, 2023

Data literacy — Employees can interpret and analyze data to draw logical conclusions; they can also identify subject matter experts best equipped to educate on specific data assets. Data governance is a key use case of the modern data stack. Who Can Adopt the Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

MARCH 14, 2024

It offers a transparent and accurate view of how data flows through the system, ensuring robust compliance. Data Transformation and Modeling Jet’s low-code environment lets your users transform and model their data within Fabric, making data preparation for analysis easy.

Analytics 52

Analytics Management Reporting Data Quality 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. The Source stage maintains raw data in its original form.

Data Transformation 54

Data Transformation Cost-Benefit Testing Data Lake 54

Wayne Yaddow

MARCH 28, 2025

To guarantee uniformity among datasets and enable precise integration, consistent data models and terminology must be established. Organizations should consult data governance committees to explicitly define and implement these standards. Fifth: It is essential to cultivate a strong culture of data governance and care.

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 Governance Data Quality Data-driven 130