IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 115

Data Governance Unstructured Data Metadata Data Lake 115

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 Big Data 119

AWS Big Data

MAY 28, 2024

Large language models (LLMs) such as Anthropic Claude and Amazon Titan have the potential to drive automation across various business processes by processing both structured and unstructured data. For getting data from Amazon Redshift, we use the Anthropic Claude 2.0 If yes, run query to extract information.

Unstructured Data 107

Unstructured Data Data Warehouse Structured Data Testing 107

Cloudera

JUNE 11, 2024

More than two-thirds of companies are currently using Generative AI (GenAI) models, such as large language models (LLMs), which can understand and generate human-like text, images, video, music, and even code. However, the true power of these models lies in their ability to adapt to an enterprise’s unique context.

Enterprise 93

Enterprise Unstructured Data Contextual Data Data-driven 93

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. It works in Salesforce just like any other native Salesforce data,” Carlson said.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. However, these wide-ranging data types are typically stored in silos across multiple data stores.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Despite being primarily an AWS shop, Rocket has taken a model-agnostic approach to generative AI platforms.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. With AWS Glue 5.0, AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

Jet Global

NOVEMBER 5, 2020

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. OLAP reporting has traditionally relied on a data warehouse. Data lakes are not a mature technology.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

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 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Cloudera

OCTOBER 29, 2020

Included with CDP Data Warehouse and Machine Learning, DV enables data engineers, data scientists, business analysts, and business users to create and share important insights instantly across any team using an intuitive drag-and-drop interface. CDP Data Visualization Connects All Your Data Across the CDP Ecosystem.

Visualization 111

Visualization Machine Learning Dashboards Data Warehouse 111

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them!

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

CIO Business Intelligence

OCTOBER 2, 2024

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. During the blending process, duplicate information can also be eliminated.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

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

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. If it’s not done right away, then later.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

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 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

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 98

Data Warehouse Cost-Benefit Unstructured Data Machine Learning 98

Sisense

MAY 28, 2019

Two orthogonal approaches to data analytics have developed in this decade of BI: 1. Operating “in-data” to enable the direct query of unstructured data lakes, providing a visualization layer on top of them. This is typically done on top of a high-performance database and, these days, on top of a cloud data warehouse.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

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.

Data Warehouse 81

Data Warehouse Experimentation Dashboards Visualization 81

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 119

Data Lake Sales Data Warehouse Snapshot 119

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.

Data Warehouse 103

Data Warehouse Cost-Benefit Unstructured Data Optimization 103

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 135

Analytics Data Science Unstructured Data Data mining 135

CIO Business Intelligence

MAY 24, 2022

The survey found the mean number of data sources per organisation to be 400, and more than 20 percent of companies surveyed to be drawing from 1,000 or more data sources to feed business intelligence and analytics systems. However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years.

Data-driven 98

Data-driven Data Lake Data Warehouse Machine Learning 98

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. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 75

Data Warehouse Data Lake Cost-Benefit Metadata 75

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 131

Analytics Data Science Statistics Unstructured Data 131

Cloudera

JANUARY 28, 2022

Open and extensible to support new clouds, data types and data services. All in a distributed cloud model that spans multi-public, private & edge clouds. . Here, I’ll provide some guidance on key considerations for a hybrid data cloud. What data do I need to achieve these objectives?

Slice and Dice 115

Slice and Dice Cost-Benefit Data Governance Risk 115

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 64

Unstructured Data Data Lake Data Warehouse Machine Learning 64

Cloudera

AUGUST 20, 2021

Analytical Outcome: CDP delivers multiple analytical outcomes including, to name a few, operational dashboards via the CDP Operational Database experience or ad-hoc analytics via the CDP Data Warehouse to help surface insights related to a business domain. A Holistic Visual Exploration of Data.

Strategy 98

Strategy Cost-Benefit Visualization Data Warehouse 98