AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Data Governance 93

Data Governance Unstructured Data Metadata Data Lake 93

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

Data Warehouse 43

Data Warehouse Unstructured Data Internet of Things Enterprise 43

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

Data Integration 88

Data Integration Data Lake Metadata Data Warehouse 88

Smart Data Collective

OCTOBER 27, 2021

The application presents a massive volume of unstructured data through a graphical or programming interface using the analytical abilities of business intelligence technology to provide instant insight. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights.

Interactive 113

Interactive Unstructured Data Analytics Data Warehouse 113

CIO Business Intelligence

OCTOBER 19, 2023

Enterprises can harness the power of continuous information flow by lessening the gap between traditional architecture and dynamic data streams. Unstructured data formatting issues Increasing data volume gets more challenging because it has large volumes of unstructured data.

Data Integration 120

Data Integration Unstructured Data Data-driven Data Warehouse 120

Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Data Lake 167

Data Lake Unstructured Data Management Analytics 167

Cloudera

SEPTEMBER 17, 2018

These trends and demands lead to stress for existing data warehouse solutions – scale, efficiency, security integrations, IT budgets, ease of access. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

Data Warehouse 53

Data Warehouse Optimization Visualization Unstructured Data 53

CIO Business Intelligence

MARCH 29, 2024

Modernizing data operations CIOs like Woodring know well that the quality of an AI model depends in large part on the quality of the data involved — and how that data is injected from databases, data warehouses, cloud data lakes, and the like into large language models.

Data Lake 118

Data Lake Machine Learning Data Warehouse Unstructured Data 118

CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Unstructured Data 60

Unstructured Data Data Lake Data Warehouse Machine Learning 60

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

FineReport

JULY 1, 2021

BI technology is a series of technologies that can handle a large amount of structured and sometimes unstructured data. Their purpose is to help identify, develop and otherwise tap the value of big data and create opportunities for new strategic businesses. Data warehouse. Data querying & discovery.

Business Intelligence 98

Business Intelligence Technology Data Warehouse Dashboards 98

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 109

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 109

CIO Business Intelligence

MAY 24, 2022

The Intelligent Data Management Cloud for Financial Services, like Informatica’s other industry-focused platforms, combines vertical-based accelerators with the company’s suite of machine learning tools to help with challenges around unstructured data and quick data-based decision making. .

Finance 134

Finance Management Metadata Data Quality 134

Timo Elliott

JANUARY 3, 2022

It’s stored in corporate data warehouses, data lakes, and a myriad of other locations – and while some of it is put to good use, it’s estimated that around 73% of this data remains unexplored. In this way, you can turn dark data into insights and help drive business improvements. Learn More.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

Insurance 83

Insurance Data Warehouse Data-driven Unstructured Data 83

CIO Business Intelligence

JULY 10, 2023

One of the ways Rokita is looking to stay ahead in the AI landscape is the creation of a new ChatGPT plugin that exposes Edmunds’ unstructured data—vehicle reviews, ratings, editorials—to the generative AI. The data warehouse is about past data, and models are about future data.

Data Warehouse 91

Data Warehouse Cost-Benefit Unstructured Data Machine Learning 91

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

SEPTEMBER 17, 2020

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data modeling basics.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 64

Data Warehouse Data Lake Cost-Benefit Modeling 64

Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

CIO Business Intelligence

SEPTEMBER 14, 2023

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.

Analytics 132

Analytics Data Science Unstructured Data Data mining 132

CIO Business Intelligence

DECEMBER 13, 2023

An example of that is a data warehouse in Azure we brought in and offer as a service. All they have to do is map their data and upload it, and then new data is refueled overnight so they can get new analytics out.” We’ve inherited some of it after reorganizations that we develop and manage.

IT 83

IT Unstructured Data Cost-Benefit Data Warehouse 83

CDW Research Hub

SEPTEMBER 15, 2020

Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Traditional data warehouses are often too slow and can’t handle large volumes of data or different types of semi-structured or unstructured data.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

IBM Big Data Hub

SEPTEMBER 19, 2022

One way to achieve real-time analytics is with a combination of a time-series database (InfluxDB or TimescaleDB) or a NoSQL database (MongoDB) + a data warehouse + a BI tool: This architecture raises a question: Why would one use an operational database, and still need a data warehouse ? But wait, it gets better….

IoT 52

IoT Analytics Data Warehouse Manufacturing 52

AWS Big Data

MARCH 25, 2024

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

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. You can monitor the job progress.

Data Lake 100

Data Lake Sales Data Warehouse Snapshot 100

Ontotext

DECEMBER 15, 2022

Most legacy approaches to data management, like relational databases and data warehouses, focus on structured data. But in the modern world, more and more data comes from unstructured sources, and here’s where knowledge graphs gain the upper hand.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. All BI software capabilities, functionalities, and features focus on data.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

Analytics 123

Analytics Data Science Statistics Unstructured Data 123

Andrew White

DECEMBER 9, 2019

Scope could be: Data (i.e. Information (processed data). Records (files, or what you might all unstructured data). Analytical stewardship is a missing link in analytics, BI and data science. Downstream in the analytics pipeline. Analytic (the analytics itself). Images (i.e. Events or transactions.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

FineReport

JULY 28, 2021

Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98