Alation

FEBRUARY 13, 2020

IDC Innovators: Data Intelligence Software Platforms, 2019 Report. In the latest IDC Innovators: Data Intelligence Software Platforms, 2019 3 report, Alation was profiled as one vendor disrupting the data integration and integrity software market with a differentiated data intelligence software platform.

Machine Learning 52

Machine Learning Big Data Data Governance Metadata 52

CIO Business Intelligence

JANUARY 5, 2024

When I joined the group in June 2019, there were two decision-making centers: Americas and the rest of the world. From an organizational standpoint, we evolved to a nearshore model, attracting the necessary talent that new technologies required. And in just eight months, we were able to put 80% of our platforms on current technologies.

IT 113

IT Finance Cost-Benefit Strategy 113

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 98

Analytics Insurance Big Data Uncertainty 98

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. They create reliable, consistent and communicable models for representing data. Schemas are powerful.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

erwin

JANUARY 30, 2020

However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions. And close to 50 percent have deployed data catalogs and business glossaries. erwin Named a Leader in Gartner 2019 Metadata Management Magic Quadrant. Stop Wasting Your Time.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

AWS Big Data

NOVEMBER 10, 2023

As a result of utilizing the Amazon Redshift integration for Apache Spark, developer productivity increased by a factor of 10, feature generation pipelines were streamlined, and data duplication reduced to zero. Johan Olivier is a Senior Machine Learning Engineer for Capitec’s Model Platform.

Data Processing 103

Data Processing Data Lake Data Warehouse Optimization 103

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 228

Modeling Machine Learning Predictive Modeling Consulting 228

erwin

DECEMBER 12, 2019

erwin Data Intelligence (erwin DI) combines data management and data governance processes in an automated flow. These connectors offer the fastest and most accurate path to data lineage, impact analysis and other detailed graphical relationships.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Ontotext

SEPTEMBER 15, 2020

Data Fabric’ has reached where ‘Cloud Computing’ and ‘Grid Computing’ once trod. Data Fabric hit the Gartner top ten in 2019. The purpose of weaving a Data Fabric is to remove the friction and cost from accessing and sharing data in the distributed ICT environment that is the norm.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Alation

FEBRUARY 13, 2020

In the study, 75% of the 770 survey respondents indicated having difficulty in locating and accessing analytic content including data, models, and metadata. Enabling workers to find the right data is crucial to promoting self-service analytics. Get the 2019 Dresner Data Catalog Study.

Business Intelligence 52

Business Intelligence Machine Learning Marketing Metadata 52

erwin

DECEMBER 12, 2019

erwin Data Intelligence (erwin DI) combines data management and data governance processes in an automated flow. These connectors offer the fastest and most accurate path to data lineage, impact analysis and other detailed graphical relationships.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Business Over Broadway

MAY 22, 2019

Remember that digital transformation is about transforming your business and operating models with technology. Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration. IoT Artificial Intelligence.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Data Science 84

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Acquired by DataRobot June 2019).

Testing 304

Testing Machine Learning Consulting Data Quality 304

Ontotext

JULY 29, 2021

The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

FineReport

MAY 13, 2020

It provides data scientists and BI executives with data mining, machine learning, and data visualization capabilities to build effective data pipelines. . It also can be used to create a predictive model for various business domains and kinds of models, such as classification, regression, and clustering. .

OLAP 105

OLAP KPI Data mining Business Intelligence 105

Ontotext

DECEMBER 30, 2022

In 2019 the market for graph databases and knowledge graphs started heating up – appearing on Gartner’s hype curves in 2018. However, developing these models from scratch for each and every solution can be slow, expensive and risky. Ontotext develops re-usable domain models as pre-packaged knowledge graphs.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Ontotext

DECEMBER 30, 2022

In 2019 the market for graph databases and knowledge graphs started heating up – appearing on Gartner’s hype curves in 2018. Getting there boils down to making aspects of development of a knowledge graph-based solution easier such as: Domain knowledge models – This is the main ingredient, the “special sauce” of knowledge graphs.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Alation

JANUARY 13, 2022

It’s in all types of data management systems, from databases to ERP tools, to data integration software. Zhamak Dehghani of Thoughtworks is widely credited with having conceived of data mesh in a blog post back in May 2019. Data mesh inverts this model with domain-driven design and product thinking.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. A typical data pipeline for machine learning.

Machine Learning 246

Machine Learning Technology Deep Learning Data Science 246

datapine

DECEMBER 28, 2021

Statistics are infamous for their ability and potential to exist as misleading and bad data. Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! Exclusive Bonus Content: Download Our Free Data Integrity Checklist.

Statistics 363

Statistics Advertising Visualization Data mining 363

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2019 was a particularly major year for the business intelligence industry. Suddenly advanced analytics wasn’t just for the analysts.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

CIO Business Intelligence

JUNE 5, 2024

Alexander Booth, assistant director of R&D for the Texas Rangers, says the data from Statcast, the Rangers’ own data sources, and the team’s use of analytics, machine learning (ML), and AI were contributing factors to the Rangers’ World Series title in 2023. Positioning revolutionized a lot of our defensive models.”

Optimization 123

Optimization Predictive Modeling Data-driven Modeling 123

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. Some cloud applications can even provide new benchmarks based on customer data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 6, 2022

Unlock Rapid Data Analysis in PowerBI With Jet. If you use Power BI alone to generate reports, the complexity of the Microsoft Dynamics data model can be an obstacle as it requires knowledge of its proprietary DAX scripting language. Data models must be refreshed either manually or on a set schedule.

Data Warehouse 52

Data Warehouse Visualization Finance Reporting 52