Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 84

Data Warehouse Cost-Benefit Metadata Data-driven 84

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Alation

FEBRUARY 13, 2020

To draw up the ShortList, Constellation Research’s Vice President and Principal Analyst Doug Henschen evaluated more than a dozen of the industry’s best data cataloging solutions, judging companies based on a combination of client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research.

Machine Learning 52

Machine Learning Big Data Data Governance Digital Transformation 52

Ontotext

JANUARY 10, 2024

And each of these gains requires data integration across business lines and divisions. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

DataKitchen

SEPTEMBER 21, 2023

.’ It’s not just about playing detective to discover where things went wrong; it’s about proactively monitoring your entire data journey to ensure everything goes right with your data. What is Data in Place? There are multiple locations where problems can happen in a data and analytic system.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Ontotext

FEBRUARY 7, 2024

However, what we usually don’t talk about when generating an asset, are the huge invisible or unplanned costs occurring at a later stage when the data needs to be made available for analysis or secondary usage. As a result, a big portion of the IT capacity in Pharma is bound by data integration.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

AWS Big Data

FEBRUARY 1, 2023

Architecturally, we chose a serverless model, and the data lake architecture action line refers to all the architectural gaps and challenging features we determined were part of the improvements. We also used AWS Lambda for data processing. To query data from REST APIs and other data sources, we used PySpark and JDBC modules.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 72

Data Strategy Strategy Data Warehouse Prescriptive Analytics 72

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 80

Management Metadata Testing Internet of Things 80

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. Take this restaurant, for example. Enterprise Knowledge Graphs and the Semantic Web.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

Ontotext

FEBRUARY 26, 2024

Bad Data Tax and the Data Bill of Rights So far, our discussion has been pretty theoretical, so we need a compelling business justification for moving in this direction. In the race to become data-driven, most efforts have resulted in a tangled web of data integrations and reconciliations across a sea of data silos.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Andrew White

JANUARY 9, 2022

Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration. A data fabric that can’t read or capture data would not work.

Analytics 64

Analytics Measurement Modeling Data-driven 64

erwin

AUGUST 31, 2023

It delivers the ability to capture and unify the business and technical perspectives of data assets, enables effective collaboration between a variety of stakeholders, and delivers metadata-driven automation to accelerate the creation and maintenance of data sources on virtually any data management platform.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

IBM Big Data Hub

AUGUST 4, 2023

In turn, they both must also have the data literacy skills to be able to verify the data’s accuracy, ensure its security, and provide or follow guidance on when and how it should be used. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

erwin

JULY 17, 2019

Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management. You need automated data mapping and cataloging through the integration lifecycle process, inclusive of data at rest and data in motion.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data observability and data lineage are complementary concepts.

Testing 130

Testing Data Governance Data Quality Data-driven 130

O'Reilly on Data

DECEMBER 19, 2018

Anomaly detection is well-known in the financial industry, where it’s frequently used to detect fraudulent transactions, but it can also be used to catch and fix data quality issues automatically. If you suddenly see unexpected patterns in your social data, that may mean adversaries are attempting to poison your data sources.

Machine Learning 261

Machine Learning Software Testing Metadata 261

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. This can involve moving data between different storage systems, databases, or applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52