Cloudera

MAY 17, 2021

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse 90

Data Warehouse Measurement Reporting Testing 90

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow automatically encrypts data in motion, and allows you to restrict data from flowing over the public internet for SaaS applications that are integrated with AWS PrivateLink , reducing exposure to security threats. He has worked with building data warehouses and big data solutions for over 13 years.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

Smart Data Collective

APRIL 8, 2020

sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates. Big data and data warehousing.

Technology 144

Technology Data Warehouse Big Data Machine Learning 144

Cloudera

JUNE 11, 2024

However, the true power of these models lies in their ability to adapt to an enterprise’s unique context. 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.

Enterprise 93

Enterprise Unstructured Data Contextual Data Data-driven 93

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. Finally, access control policies also need to be extended to the unstructured data objects and to vector data stores.

Data Governance 124

Data Governance Unstructured Data Metadata Data Lake 124

CIO Business Intelligence

AUGUST 18, 2022

Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

CIO Business Intelligence

OCTOBER 2, 2024

And Doug Shannon, automation and AI practitioner, and Gartner peer community ambassador, says the vast majority of enterprises are now focused on two categories of use cases that are most likely to deliver positive ROI. Classifiers are provided in the toolkits to allow enterprises to set thresholds. “We

Management 141

Management Data Governance Cost-Benefit Structured Data 141

CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data-driven 54

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. 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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

David Menninger's Analyst Perspectives

SEPTEMBER 19, 2024

Snowflake was founded in 2012 to build a business around its cloud-based data warehouse with built-in data-sharing capabilities. Snowflake has expanded its reach over the years to address data engineering and data science, and long ago moved beyond being seen as just a cloud data warehouse.

Data Warehouse 130

Data Warehouse Data Science Modeling Data Governance 130

AWS Big Data

MAY 28, 2024

The details of each step are as follows: Populate the Amazon Redshift Serverless data warehouse with company stock information stored in Amazon Simple Storage Service (Amazon S3). Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 118

Unstructured Data Data Warehouse Structured Data Testing 118

IBM Big Data Hub

APRIL 24, 2023

Additionally, the increase in online transactions and web traffic generated mountains of data. Enter the modernization of data warehousing solutions. Companies realized that their legacy or enterprise data warehousing solutions could not manage the huge workload.

Data Warehouse 88

Data Warehouse Data Lake Cost-Benefit Big Data 88

CIO Business Intelligence

NOVEMBER 14, 2022

The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more. The size of the DSS database will vary based on need, from a small, standalone system to a large data warehouse. Model-driven DSS.

Data mining 144

Data mining Data-driven Statistics OLAP 144

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

AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. For our solution, we use Amazon Redshift to store the data.

Data Lake 119

Data Lake Data Warehouse Big Data Structured Data 119

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

That’s just one of the many ways to define the uncontrollable volume of data and the challenge it poses for enterprises if they don’t adhere to advanced integration tech. As well as why data in silos is a threat that demands a separate discussion. This post handpicks various challenges for existing integration solutions.

Data Integration 126

Data Integration Unstructured Data Data-driven Data Warehouse 126

FineReport

DECEMBER 27, 2021

Modern enterprise business intelligence (BI) tools and practices enable quick decision making. What is enterprise business intelligence? Business intelligence is the collection, storage, and analysis of data from firm activities to create a holistic perspective of a business. Enterprise BI vs. Self-service BI. Definition.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

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

APRIL 14, 2022

With data-driven decisions and digital services at the center of most businesses these days, enterprises can never get enough data to fuel their operations. But not every bit of data that could benefit a business can be readily produced, cleansed, and analyzed by internal means. Who needs data as a service (DaaS)?

Enterprise 138

Enterprise Marketing Measurement Reporting 138

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Prantik specializes in architecting modern data and analytics platforms in AWS.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. Why Enterprise Knowledge Graphs? Knowledge graphs offer a smart way out of these challenges.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Jet Global

NOVEMBER 5, 2020

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

AWS Big Data

MARCH 27, 2024

You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse. This will be your online transaction processing (OLTP) data store for transactional data. With continuous innovations added to Amazon Redshift, it is now more than just a data warehouse.

Data Analytics 119

Data Analytics Analytics Data Warehouse Data Lake 119

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

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. connection testing, metadata retrieval, and data preview.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

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

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. Langchain) and LLM evaluations (e.g.

Management 80

Management Metrics Data Processing Machine Learning 80

FineReport

JUNE 24, 2021

Business intelligence solutions are a whole combination of technology and strategy, used to handle the existing data of the enterprises effectively. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

Data Lake 111

Data Lake Big Data Data Warehouse Consulting 111

Ontotext

OCTOBER 14, 2021

Investment firms, including one of Ontotext’s clients, spend enormous sums every year buying data from brokers, while also producing original analyses and relying on coverage from news media, especially in regions where raw numbers are harder to find. See figure 1.). Mock Knowledge Graph for New Delhi Ventures. What is an ontology?

Reporting 98

Reporting Structured Data Data Warehouse Metadata 98

AWS Big Data

FEBRUARY 20, 2024

The elasticity of Kinesis Data Streams enables you to scale the stream up or down, so you never lose data records before they expire. Analytical data storage The next service in this solution is Amazon Redshift, a fully managed, petabyte-scale data warehouse service in the cloud.

Visualization 124

Visualization Cost-Benefit Optimization B2B 124

CDW Research Hub

JANUARY 21, 2021

Its ability to natively load and use SQL to query semi-structured and structured data within a single system simplifies your data engineering. At Sirius, we’re piloting a modern analytic solution using Snowflake’s scalable cloud data warehouse in combination with ThoughtSpot through its Partner Connect service offering.

Data Warehouse 52

Data Warehouse Dashboards Predictive Analytics Structured Data 52

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. About the Authors Ismail Makhlouf is a Senior Specialist Solutions Architect for Data Analytics at AWS.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98