Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

JUNE 22, 2023

This will minimize the risk of investing resources in fundamentally wrong assumptions and will give researchers more confidence to choose top targets for validation. Its user-friendly and customizable nature enables users to explore the data visually and provides metrics that automate target ranking and reduce risks.

Metrics 52

Metrics Statistics Visualization Metadata 52

Octopai

MARCH 22, 2023

This can be more cost-effective than traditional data warehousing solutions that require a significant upfront investment. Support for multiple data structures. Unlike traditional data warehouse platforms, snowflake supports both structured and semi-structured data.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

Octopai

JUNE 26, 2020

This helps establish clear processes for effective data management throughout the enterprise. Enterprise data governance tools also work to prevent the adverse effects of poor data quality and aim to ensure that the entire enterprise can actually use its data. Automated metadata governance.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

bridgei2i

FEBRUARY 21, 2019

Traditional algorithmic solutions around structured data have gained and continue to gain traction. A textbook example of t raditional analytics techniques revolving around structured data in global enterprise sales organizations. Voice data quality). Examples of AI Solutions Usage.

Sales 40

Sales Structured Data Forecasting Enterprise 40

Peter James Thomas

AUGUST 29, 2018

However, in reality, the CDO role encompasses Enterprise Data Management, although generally speaking the EDM role includes responsibility for the day to day operations of the collection processes, which in my current role I don’t have. This is where the process efficiency impacts good data collection.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

MARCH 9, 2022

Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio. They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics.

Data Lake 109

Data Lake Unstructured Data Data Warehouse Data Quality 109

Alation

OCTOBER 28, 2021

Leaders are asking how they might use data to drive smarter decision making to support this new model and improve medical treatments that lead to better outcomes. Yet this is not without risks. To make good on this potential, healthcare organizations need to understand their data and how they can use it.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

erwin

OCTOBER 24, 2019

The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires. Organizations then can take a data-driven approach to business transformation , speed to insights, and risk management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Alation

OCTOBER 21, 2021

Just as lakes benefit from the filtering power of surrounding rocks, roots, and soil to sift out incoming impurities, data lakes benefit from a diligent effort to prevent them from becoming a dumping ground for all and any data. Ungoverned data. Data governance helps keep data quality high and data literacy efforts on track.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Domino Data Lab

MARCH 3, 2019

There are essentially four types encountered: image/video, audio, text, and structured data. Those later stages are where organizations gain key insights, competitive capabilities, and recognize return on investment for data science. In any case, there’s a kind of survival analysis for AI adoption.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 45

Big Data Data Lake Internet of Things Enterprise 45

erwin

AUGUST 31, 2023

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. Embracing the future In the dynamic world of data, data modeling remains an indispensable tool.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data.

Unstructured Data 108

Unstructured Data Cost-Benefit Metadata Machine Learning 108

Jet Global

MAY 9, 2024

ETL pipelines are commonly used in data warehousing and business intelligence environments, where data from multiple sources needs to be integrated, transformed, and stored for analysis and reporting. Data pipelines enable data integration from disparate healthcare systems, transforming and cleansing the data to improve data quality.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52