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. Big data is cool again.

IT 97

IT Data Architecture Unstructured Data Big Data 97

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

AUGUST 15, 2023

Some examples include AWS data analytics services such as AWS Glue for data integration, Amazon QuickSight for business intelligence (BI), as well as third-party software and services from AWS Marketplace. We create an S3 bucket to store data that exceeds the Lambda function’s response size limits.

Recreation/Entertainment 84

Recreation/Entertainment Unstructured Data Business Intelligence Data-driven 84

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

Rita Sallam

JULY 22, 2016

By contrast, traditional BI platforms are designed to support modular development of IT-produced analytic content, specialized tools and skills, and significant upfront data modeling, coupled with a predefined metadata layer, is required to access their analytic capabilities. Answer: Better than every other vendor?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

IBM Big Data Hub

JANUARY 17, 2023

These new technologies and approaches, along with the desire to reduce data duplication and complex ETL pipelines, have resulted in a new architectural data platform approach known as the data lakehouse – offering the flexibility of a data lake with the performance and structure of a data warehouse.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Smart Data Collective

SEPTEMBER 26, 2021

Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working with massive structured and unstructured data sets can turn out to be complicated. It’s a good idea to record metadata.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

FineReport

FEBRUARY 5, 2020

Nowadays, the business intelligence market is heating up. Both the investment community and the IT circle are paying close attention to big data and business intelligence. Overall, as users’ data sources become more extensive, their preferences for BI are changing. Metadata management.

Metadata 98

Metadata Dashboards Informatics Visualization 98

CIO Business Intelligence

JUNE 14, 2023

Big data exploded onto the scene in the mid-2000s and has continued to grow ever since. Today, the data is even bigger, and managing these massive volumes of data presents a new challenge for many organizations. Even if you live and breathe tech every day, it’s difficult to conceptualize how big “big” really is.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

AWS Big Data

JUNE 9, 2023

Despite these capabilities, data lakes are not databases, and object storage does not provide support for ACID processing semantics, which you may require to effectively optimize and manage your data at scale across hundreds or thousands of users using a multitude of different technologies.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

erwin

JUNE 27, 2019

Additional challenges, such as increasing regulatory pressures – from the General Data Protection Regulation (GDPR) to the Health Insurance Privacy and Portability Act (HIPPA) – and growing stores of unstructured data also underscore the increasing importance of a data modeling tool.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca choose Apache Iceberg?

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

Domino Data Lab

JANUARY 21, 2021

Additionally, the Python ecosystem is flush with open source development projects that maintain the language’s relevancy in the face of new techniques in the field of data science. It’s worth noting that there is a landscape of proprietary tools dedicated to producing descriptive analytics in the name of business intelligence.

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

AWS Big Data

FEBRUARY 21, 2023

It is a data modeling methodology designed for large-scale data warehouse platforms. What is a data vault? The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

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 67

Data Architecture Data Lake Machine Learning Data Governance 67