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.

Unstructured Data 89

Unstructured Data IoT Metadata Manufacturing 89

Rocket-Powered Data Science

JULY 19, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

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

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

erwin

SEPTEMBER 10, 2020

Yet given this era of digital transformation and fierce competition, understanding what data you have, where it came from, how it’s changed since creation or acquisition, and whether it poses any risks is paramount to optimizing its value. Data Lineage Tells an Important Origin Story. Who are the data owners?

Data Governance 131

Data Governance Key Performance Indicator Digital Transformation Metadata 131

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 94

Data Lake Unstructured Data Data Warehouse Data Quality 94

CIO Business Intelligence

DECEMBER 4, 2023

A modern information lifecycle management approach Today’s ILM approach recognizes the enterprise value of all digitized and enriched assets , avoiding the habituated, narrow reliance ontraditional structured data. Here is a high-level overview of the ILM steps and structure. Structure/Operationalize. Preserve/Dispose.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts. Why do risk and opportunity events matter?

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Alation

OCTOBER 21, 2021

That dirty data then corrupts analyses and forces mistakes. A frequent and periodic data cleansing strategy is. Lack of metadata. A lack of organization is another sign of a data swamp, typically driven by bad or incomplete metadata. So what is a Data Lakehouse?

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 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. Ensuring the complete removal of data from all these copies and backups can be challenging.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Enrichment typically involves adding demographic, behavioral, and geolocation data.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Ontotext

MAY 5, 2023

Here, the ability of knowledge graphs to integrate diverse data from multiple sources is of high relevance. As you can see from the slide below, knowledge graphs can provide a single access point for various types of data such as structured data, knowledge organization systems, transactional data and signals from unstructured content.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

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. Another problem in drug development is that although companies gather a lot of data from multiple databases, they struggle to derive key insights about safety, drugability, etc.

Metrics 52

Metrics Statistics Visualization Metadata 52

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

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.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

CIO Business Intelligence

MARCH 6, 2023

We use Snowflake very heavily as our primary data querying engine to cross all of our distributed boundaries because we pull in from structured and non-structured data stores and flat objects that have no structure,” Frazer says. “We think we found a good balance there. Now that’s down to a number of hours.”

Data Lake 58

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 58

Ontotext

MARCH 22, 2024

Each sample was annotated by three independent annotators using Ontotext Metadata Studio (OMDS). Structured data = better insights The extracted events conform to a structure defined by the event schema. To ensure the high quality of the annotations, we followed principles towards designing a Gold Standard corpus.

Modeling 59

Modeling Metadata Structured Data Risk 59

AWS Big Data

DECEMBER 21, 2023

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets.

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

Cloudera

SEPTEMBER 6, 2018

Handle increases in data volume gracefully. Represent entity relationships, to help determine ultimate beneficial owner, contribute to risk scoring, and facilitate investigations. Provide audit and data lineage information to facilitate regulatory reviews. Entity Resolution and Data Enrichment. Entity Risk Scoring.

Machine Learning 40

Machine Learning Big Data Risk Unstructured Data 40

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 44

Big Data Data Lake Internet of Things Enterprise 44

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

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61