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

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. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

DECEMBER 13, 2023

Applications such as financial forecasting and customer relationship management brought tremendous benefits to early adopters, even though capabilities were constrained by the structured nature of the data they processed. have encouraged the creation of unstructured data. What’s hiding in your unstructured data?

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

Octopai

SEPTEMBER 21, 2020

A crucial part of every company’s business intelligence (BI) is its data dictionary. When you have a well-structured data dictionary, you provide BI teams with an easy way to track and manage metadata throughout the entire enterprise. For example, healthcare companies rely on efficient, structured BI catalogs.

Metadata 52

Metadata Enterprise Structured Data Business Intelligence 52

erwin

SEPTEMBER 10, 2020

As I mentioned above, the three Vs of data and the integration of systems makes it difficult to understand the resulting data web much less capture a simple visual of that flow. Yet a consistent view of data and how it flows is paramount to the success of enterprise data governance and any data-driven initiative.

Data Governance 131

Data Governance Key Performance Indicator Digital Transformation Metadata 131

Ontotext

SEPTEMBER 15, 2020

The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

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 68

Analytics Data Warehouse Data Lake Metadata 68

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., internal metadata, industry ontologies, etc.)

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Octopai

FEBRUARY 8, 2020

While some businesses suffer from “data translation” issues, others are lacking in discovery methods and still do metadata discovery manually. Moreover, others need to trace data history, get its context to resolve an issue before it actually becomes an issue. The solution is a comprehensive automated metadata platform.

Metadata 63

Metadata Key Performance Indicator Unstructured Data Business Intelligence 63

CIO Business Intelligence

DECEMBER 4, 2023

When you enrich, structure, and operationalize data on the way in, there is no limit to the efficiencies, value streams, and insights unlocked by readily available powerful cloud platform tools. The ways modern data is used, processed, and analyzed are continuously evolving as machine learning technology becomes better at these tasks.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

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

Octopai

MAY 30, 2019

The Benefits of Structured Data Catalogs. At the most basic level, data catalogs help you organize your company’s massive datasets. Most enterprises have huge data lakes with millions of touchpoints all living in the dark. Choosing a Data Catalog. Consider your data sources here ( on prem , cloud, etc.)

Metadata 40

Metadata Data Governance Data Lake IoT 40

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 106

IT Data Architecture Unstructured Data Big Data 106

CIO Business Intelligence

JUNE 23, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 97

IT Data Architecture Unstructured Data Big Data 97

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

Ontotext

DECEMBER 15, 2022

Today’s enterprises are increasingly daunted by the realization that more data doesn’t automatically equal deeper knowledge and better business decisions. Obviously, not all of that data is accessible to businesses, but what they can access is still overwhelming. Enter metadata. Connecting the dots of data of all types.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

AWS Big Data

MARCH 13, 2024

AWS Glue crawls both S3 bucket paths, populates the AWS Glue database tables based on the inferred schemas, and makes the data available to other analytics applications through the AWS Glue Data Catalog. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 90

Analytics IoT Metadata Internet of Things 90

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. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

BizAcuity

MARCH 29, 2019

Data in healthcare industry can be broadly classified into two sources: clinical data and claims data. Claims data comes from the payers, containing extremely uniform and structured data about patients receiving care, their demographics and the care setting they are in.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

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

AWS Big Data

APRIL 2, 2024

Additionally, data owners and data stewards can make data discovery simpler by adding business context to data while balancing access governance to the data in the user interface. The recommendations don’t use any data that resides in the tables unless explicitly provided by the user as content in the metadata.

Metadata 85

Metadata Metrics Data-driven Modeling 85

Ontotext

SEPTEMBER 7, 2023

But the best way to do it from an enterprise standpoint is to think that this project will grow into a practice. People realize more and more that if they can connect their knowledge graph to everything else, they can get a lot more power by having all this data brought together, not just as a one-off solution.

Technology 59

Technology Visualization Digital Transformation Management 59

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

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. The following diagram illustrates an example workflow for CDC streaming ingestion and processing for unified customer profiles. versions).

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

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. Helping organisations become “data-centric” is a key part of what you do.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. Data catalogs and spreadsheets are related in many ways.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Tags provide metadata about resources at a glance. You can contact us with questions.

Snapshot 79

Snapshot Metadata Measurement Data Warehouse 79

AWS Big Data

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type.

Cost-Benefit 82

Cost-Benefit Metadata Structured Data Management 82

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

FineReport

FEBRUARY 5, 2020

As a part of enterprise informationization, there are many reasons for BI platform to do separate management and disaster recovery. On the one hand, governments, Internet companies, and large enterprises attach great importance to informatization construction and require separate maintenance. Metadata management.

Metadata 98

Metadata Dashboards Informatics Visualization 98

Ontotext

OCTOBER 14, 2021

For the purposes of this article, you just need to know the following: A graph is a method of storing and modeling data that uniquely captures the relationships between data. A knowledge graph uses this format to integrate data from different sources while enriching it with metadata that documents collective knowledge about the data.

Reporting 98

Reporting Structured Data Metadata Data Warehouse 98

erwin

APRIL 18, 2019

An effective data governance initiative should enable just that, by giving an organization the tools to: Discover data: Identify and interrogate metadata from various data management silos. Harvest data: Automate the collection of metadata from various data management silos and consolidate it into a single source.

Data Governance 81

Data Governance Metadata Data-driven Data Collection 81

Octopai

FEBRUARY 27, 2020

The business intelligence & analytics environment becomes further complex when you consider the multiple systems in place processing data (database (DWH), ETL, analysis, reporting) that are all likely housing different descriptions of the same data, creating ONE. Want to acquire better data insights? The Octopai Difference.

Metadata 52

Metadata Data Warehouse Reporting Software 52

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 Data Quality 119

Alation

JULY 19, 2022

A data catalog can assist directly with every step, but model development. And even then, information from the data catalog can be transferred to a model connector , allowing data scientists to benefit from curated metadata within those platforms. How Data Catalogs Help Data Scientists Ask Better Questions.

Metadata 59

Metadata Data Quality Statistics Data Science 59