CIO Business Intelligence

MARCH 21, 2022

Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientist job description. Semi-structured data falls between the two.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Structured Data 137

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 114

Data Lake Data Processing Metadata Snapshot 114

Cloudera

JUNE 7, 2022

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. Where data flows, ideas follow.

IT 106

IT Data Architecture Unstructured Data Big Data 106

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

CIO Business Intelligence

JUNE 23, 2022

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. But this is not your grandfather’s big data.

IT 97

IT Data Architecture Unstructured Data Big Data 97

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Consulting Enterprise 78

Octopai

JUNE 24, 2019

Document classification and lifecycle management will help you deal with oversight of unstructured data. – Data management : As part of maintaining the integrity of your data, it will be necessary to track activities. This maintains a high priority in your data governance strategy.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

AWS Big Data

MARCH 7, 2024

You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can also store other data in purpose-built data stores to analyze and get fast insights from both structured and unstructured data.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

Alation

JUNE 2, 2022

A data catalog is a central hub for XAI and understanding data and related models. While “operational exhaust” arrived primarily as structured data, today’s corpus of data can include so-called unstructured data. Data management can never be a pure, complete process. Other Technologies. The challenge?

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

Sisense

MAY 28, 2020

As enterprises demand data infrastructures that can meet this growth in real-time data — and ultimately assist with their product differentiation strategy — the pressure put on product teams is huge. Product teams are already having to manage the growing complexities that come with modern data environments.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

IBM Big Data Hub

FEBRUARY 14, 2024

Promote cross- and up-selling Recommendation engines use consumer behavior data and AI algorithms to help discover data trends to be used in the development of more effective up-selling and cross-selling strategies, resulting in more useful add-on recommendations for customers during checkout for online retailers.

Cost-Benefit 89

Cost-Benefit Insurance Unstructured Data Machine Learning 89

CIO Business Intelligence

MARCH 29, 2022

. • You have data but don’t use it. Why does valuable data so often go unused? Lack of annotation with the right metadata is a contributing factor. An even larger issue is that people may not know how to see value in data. Recognizing what data can tell you is an acquired skill for people beyond just data scientists.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

AWS Big Data

JANUARY 8, 2024

Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer. It provides the ability to collect data from tens of thousands of data sources and ingest in real time.

Analytics 109

Analytics IoT Data-driven Snapshot 109

O'Reilly on Data

FEBRUARY 11, 2020

They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. An additional 7% are data engineers.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

CDW Research Hub

AUGUST 17, 2020

It’s the most simplistic version of storage—you give files a name, tag them with metadata, and organize them into directories and subdirectories. But here’s the caveat: storage at the file level can handle only small amounts of data. Block storage stores data files on storage area networks (SANs). So, what is file storage?

Unstructured Data 97

Unstructured Data Metadata Manufacturing Enterprise 97

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Working with massive structured and unstructured data sets can turn out to be complicated. Preserve information: Keep your raw data raw.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

Ontotext

MARCH 23, 2023

While the topic has gotten a lot of buzz, a data fabric is not a specific application or software package you download and solve all your data management challenges. Instead, it’s a set of principles and strategies that enable the seamless integration and management of data across multiple platforms and sources.

Management 52

Management Metadata Unstructured Data Data Integration 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 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

FEBRUARY 1, 2024

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required. It is continuously updated.

Metadata 92

Metadata Modeling Data Processing Unstructured Data 92

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

Snapshot 80

Snapshot Data Lake Testing Strategy 80

FineReport

FEBRUARY 5, 2020

Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis.

Metadata 98

Metadata Dashboards Informatics Visualization 98

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Alation

MARCH 21, 2023

Organizations in the travel and tourism vertical use big data and analytics to find patterns in structured and unstructured data that allow them to make informed business decisions. What are common data challenges for the travel industry? They may also suffer from data duplication, which undermines their analytics models.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

JUNE 9, 2023

Iceberg doesn’t optimize file sizes or run automatic table services (for example, compaction or clustering) when writing, so streaming ingestion will create many small data and metadata files. Offers different query types , allowing to prioritize data freshness (Snapshot Query) or read performance (Read Optimized Query).

Data Lake 109

Data Lake Metadata Optimization Statistics 109

Ontotext

FEBRUARY 26, 2024

Understanding how certain types of events have historically affected their stock prices can guide future business decisions and communication strategies. Quality assurance process, covering gold standard creation , extraction quality monitoring, measurement, and reporting via Ontotext Metadata Studio.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Ontotext

SEPTEMBER 2, 2020

There must be a strategy and a practice for preserving the knowledge, to create institutional memory. Instead, it creates a unified way, sometimes called a data fabric, of accessing an organization’s data as well as 3rd party or global data in a seamless manner. Knowledge graphs can help do both.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

AWS Big Data

FEBRUARY 21, 2023

We dive deep into a hybrid approach that aims to circumvent the issues posed by these two and also provide recommendations to take advantage of this approach for healthcare data warehouses using Amazon Redshift. What is a dimensional data model? It optimizes the database for faster data retrieval.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

AWS Big Data

JULY 20, 2023

To overcome these issues, Orca decided to build a data lake. A data lake is a centralized data repository that enables organizations to store and manage large volumes of structured and unstructured data, eliminating data silos and facilitating advanced analytics and ML on the entire data.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. What is a Data Governance Strategy?

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement. How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Alation

FEBRUARY 10, 2022

Let’s discuss what data classification is, the processes for classifying data, data types, and the steps to follow for data classification: What is Data Classification? Either completed manually or using automation, the data classification process is based on the data’s context, content, and user discretion.

Data Governance 52

Data Governance Risk Insurance Strategy 52

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 88

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 88

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 66

Data Architecture Data Lake Machine Learning Data Governance 66