Ontotext

JULY 29, 2021

The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data? What is it? Which Semantic Web?

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

O'Reilly on Data

DECEMBER 19, 2018

We won’t be writing code to optimize scheduling in a manufacturing plant; we’ll be training ML algorithms to find optimum performance based on historical data. If humans are no longer needed to write enterprise applications, what do we do? We are starting to see some tools that automate data quality issues.

Machine Learning 279

Machine Learning Software Metadata Testing 279

CIO Business Intelligence

SEPTEMBER 19, 2024

Data intelligence platform vendor Alation has partnered with Salesforce to deliver trusted, governed data across the enterprise. It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud.

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

OCTOBER 2, 2024

And Doug Shannon, automation and AI practitioner, and Gartner peer community ambassador, says the vast majority of enterprises are now focused on two categories of use cases that are most likely to deliver positive ROI. Classifiers are provided in the toolkits to allow enterprises to set thresholds. “We

Management 141

Management Data Governance Cost-Benefit Structured Data 141

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

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. Why Enterprise Knowledge Graphs? Knowledge graphs offer a smart way out of these challenges.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. This isn’t an easy task.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Cloudera

NOVEMBER 15, 2021

The International Data Corporation (IDC) estimates that by 2025 the sum of all data in the world will be in the order of 175 Zettabytes (one Zettabyte is 10^21 bytes). Most of that data will be unstructured, and only about 10% will be stored. Data curation. Addressing the challenges of data. Less will be analysed.

Unstructured Data 90

Unstructured Data Recreation/Entertainment Structured Data Reporting 90

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Prantik specializes in architecting modern data and analytics platforms in AWS.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

BizAcuity

MARCH 29, 2019

Load data into staging, perform data quality checks, clean and enrich it, steward it, and run reports on it completing the full management cycle. Numbers are only good if the data quality is good. Data in healthcare industry can be broadly classified into two sources: clinical data and claims data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

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. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 97

Analytics Data Warehouse Data Lake Metadata 97

Timo Elliott

JANUARY 22, 2019

As business applications move to the cloud, and external data becomes more important, cloud analytics becomes a natural part of enterprise architectures. But it magnifies any existing problems with data quality and data bias and poses unprecedented challenges to privacy and ethics. New experience analytics.

Analytics 96

Analytics Machine Learning Unstructured Data Business Intelligence 96

Ontotext

MAY 30, 2019

Which are not so different from the concerns of any other enterprise having to deal with data management. And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet.

Cost-Benefit 87

Cost-Benefit Big Data Technology Metadata 87

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

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 102

Data Strategy Strategy Data Warehouse Prescriptive Analytics 102

Ontotext

SEPTEMBER 15, 2020

Connecting the data in a graph allows concepts and entities to complement each other’s description. Given a critical mass of domain knowledge and good level of connectivity, KG can serve as context that helps computers comprehend and manipulate data. Ontotext’s Platform for Enterprise Knowledge Graphs.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

MAY 30, 2019

Which are not so different from the concerns of any other enterprise having to deal with data management. And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet.

Cost-Benefit 75

Cost-Benefit Big Data Technology Metadata 75

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 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Alation

JULY 19, 2022

Modern data catalogs also facilitate data quality checks. Historically restricted to the purview of data engineers, data quality information is essential for all user groups to see. Data scientists often have different requirements for a data catalog than data analysts.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Ontotext

JANUARY 10, 2024

The reason is that the inherent complexity of big enterprises is such that this is the simplest model that enables them to “connect the dots” across the different operational IT systems and turn the diversity of their business into a competitive advantage. This requires new tools and new systems, which results in diverse and siloed data.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Wayne Yaddow

MARCH 14, 2025

The early detection and prevention method is essential for businesses where data accuracy is vital, including banking, healthcare, and compliance-oriented sectors. dbt Cloud vs. dbt Core: Data Transformations TestingFeatures dbt Cloud and dbt Core Data TestingFeatures Some Testing Features Missing From dbt Core: How ToMitigate 1.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

Ontotext

JANUARY 6, 2021

A knowledge graph can be used as a database because it structures data that can be queried such as through a query language like SPARQL. Reuse of knowledge from third party data providers and establishing data quality principles to populate it. The connections made through these descriptions create context.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 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 Data Quality 40

Alation

JUNE 2, 2022

Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. A data catalog is a central hub for XAI and understanding data and related models. And until recently, such governance processes have been fragmented. Other Technologies.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

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. What is Big Data Fabric?

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

DataRobot Blog

APRIL 1, 2018

In Nick Heudecker’s session on Driving Analytics Success with Data Engineering , we learned about the rise of the data engineer role – a jack-of-all-trades data maverick who resides either in the line of business or IT. 3) The emergence of a new enterprise information management platform.

Analytics 40

Analytics IoT Internet of Things Machine Learning 40

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., Transaction and pricing data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Peter James Thomas

AUGUST 29, 2018

I know you have a strong background in Enterprise Data Management , how does the CDO role differ from this area? I guess that depends on how you determine the scope of Enterprise Data Management. My role today boils down to 4 key objectives – data availability, data transparency, data quality and data control.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

FineReport

JULY 18, 2022

Here I list 15 excellent tools for data analysis, among which there must be the one that fits you best. FineReport is a business intelligence reporting and dashboard software that helps enterprises transform data into value. It also has a commercial version for enterprises. FineRepor t. From FineReport. Free Download.

Forecasting 52

Forecasting Dashboards Statistics Visualization 52

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain data quality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

O'Reilly on Data

APRIL 19, 2021

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The biggest problems in this year’s survey are lack of skilled people and difficulty in hiring (19%) and data quality (18%). Bad data yields bad results at scale.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Alation

OCTOBER 21, 2021

Many organizations have built a data lake to solve their data storage, access, and utilization challenges. A data lake is a centralized repository used to store data of many types at enterprise scale, which then enables easy access for many business needs. Signs Your Data Lake is Actually a Data Swamp.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Jet Global

MAY 9, 2024

Data pipelines can serve various purposes beyond ETL, such as real-time analytics, machine learning, and stream processing applications. ETL pipelines are designed to prepare data for analysis, reporting, or other business intelligence applications. What is an ETL pipeline? How is ELT different from ETL?

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52