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. Data management, when done poorly, results in both diminished returns and extra costs.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

Timo Elliott

FEBRUARY 6, 2025

I recently had the opportunity to interview Robert Reuben, Managing Director of Proceed Group. In an era where data is both a critical asset and a growing challenge, he shared insights into how his organization helps businesses optimize their data landscapes, overcome common pitfalls, and prepare for the future.

Management 52

Management Unstructured Data Data Warehouse Optimization 52

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 178

Data Lake Unstructured Data Management Analytics 178

DataKitchen

APRIL 13, 2021

Testing and Data Observability. Sandbox Creation and Management. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Sandbox Creation and Management.

Testing 300

Testing Machine Learning Consulting Data Science 300

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

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. It’s a different beast to manage workloads in the cloud versus workloads on premise. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

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

Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

David Menninger's Analyst Perspectives

OCTOBER 31, 2024

It was not until the addition of open table formats— specifically Apache Hudi, Apache Iceberg and Delta Lake—that data lakes truly became capable of supporting multiple business intelligence (BI) projects as well as data science and even operational applications and, in doing so, began to evolve into data lakehouses.

Data Lake 130

Data Lake Unstructured Data Data Warehouse Software 130

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. AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109

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

CIO Business Intelligence

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

APRIL 19, 2023

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

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 119

Data Integration Data Lake Data Warehouse Metadata 119

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. The complexity doesn’t end here.

Data Integration 126

Data Integration Unstructured Data Data-driven Data Warehouse 126

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

Cloudera

JUNE 11, 2024

By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and objectives. Structured data is highly organized and formatted in a way that makes it easily searchable in databases and data warehouses.

Enterprise 93

Enterprise Unstructured Data Contextual Data Data-driven 93

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

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

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. Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 102

Unstructured Data Data Warehouse Structured Data Testing 102

Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

Data mining 307

Data mining Data Collection Strategy Data Analytics 307

Jet Global

NOVEMBER 5, 2020

If your company is using Microsoft Dynamics AX, you’ll be aware of the company’s shift to Microsoft Dynamics 365 Finance and Supply Chain Management (D365 F&SCM). OLAP reporting has traditionally relied on a data warehouse. Unfortunately, Microsoft is not providing that kind of data warehouse solution out of the box.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

CIO Business Intelligence

JUNE 29, 2022

Analytics is the means for discovering those insights, and doing it well requires the right tools for ingesting and preparing data, enriching and tagging it, building and sharing reports, and managing and protecting your data and insights. Azure Data Factory. Azure Data Lake Analytics. Azure Synapse Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

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

Cloudera

AUGUST 31, 2020

Service Management Group ( SMG ) offers an easy-to-use experience management (XM) platform that combines end-to-end customer and employee experience management software with hands-on professional services to deliver actionable insights and help brands get smarter about their customers. The case for a new Data Warehouse?

Management 66

Management Slice and Dice Data Warehouse Analytics 66

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. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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 manage data quality requirements?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

Cloudera

OCTOBER 29, 2020

With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.

Visualization 111

Visualization Machine Learning Dashboards Data Warehouse 111

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 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

CIO Business Intelligence

SEPTEMBER 14, 2023

These include: Generalist: Data engineers who typically work for small teams or small companies wear many hats as one of the few “data-focused” people in the company. These generalists are often responsible for every step of the data process, from managing data to analyzing it.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

AWS Big Data

JUNE 26, 2024

Last week, we announced the general availability of custom AWS service blueprints , a new feature in Amazon DataZone allowing you to customize your Amazon DataZone project environments to use existing AWS Identity and Access Management (IAM) roles and AWS services to embed the service into your existing processes.

Data Lake 102

Data Lake Data Warehouse Unstructured Data Data Governance 102

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Clearly documents data catalog policies, rules and shares information assets.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

datapine

FEBRUARY 22, 2022

These steps are imperative for businesses, of all sizes, looking to successfully launch and manage their business intelligence. Improved risk management: Another great benefit from implementing a strategy for BI is risk management. We love that data is moving permanently into the C-Suite. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

CIO Business Intelligence

AUGUST 9, 2022

These include: Generalist: Data engineers who typically work for small teams or small companies wear many hats as one of the few “data-focused” people in the company. These generalists are often responsible for every step of the data process, from managing data to analyzing it. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131