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

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Big data and data warehousing.

Technology 144

Technology Data Warehouse Big Data Machine Learning 144

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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

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

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

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

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. 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.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

APRIL 25, 2022

“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business. Features focus on media and entertainment firms.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 97

Analytics Data Warehouse Data Lake Metadata 97

CIO Business Intelligence

MAY 10, 2022

Customer data platform defined. A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Treasure Data CDP. These profiles help you understand each customer’s journey.

Advertising 122

Advertising Interactive Marketing Structured Data 122

CIO Business Intelligence

APRIL 14, 2022

DaaS vendors can also improve the quality of data that an organization might otherwise gather itself by correcting errors or filling in gaps and even provide big blocks of data should you need more. In this way, DaaS providers can improve your homegrown data warehouse by cross-fertilizing it with other, curated sources.

Enterprise 138

Enterprise Marketing Measurement Reporting 138

CDW Research Hub

DECEMBER 4, 2019

There are many benefits of using a cloud-based data warehouse, and the market for cloud-based data warehouses is growing as organizations realize the value of making the switch from an on-premises data warehouse.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

CDW Research Hub

APRIL 20, 2020

Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications.

Data Warehouse 52

Data Warehouse Data-driven Consulting 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. Let’s find out what role each of these components play in the context of C360.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

Cloudera

APRIL 1, 2024

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Cloudera

JANUARY 11, 2018

Data science and advanced analytics deliver more value if organizations can deploy models and algorithms on detailed data brought together from many sources, not just on summaries or samples contained in a single data warehouse or data mart.” ” And teases at the reward.

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40

Cloudera

OCTOBER 3, 2018

In the data center and in the cloud, there’s a proliferation of players, often building on technology we’ve created or contributed to, battling for share. The tremendous growth in both unstructured and structured data overwhelms traditional data warehouses. We have each innovated separately in those areas.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Over the years, he has helped multiple customers on data platform transformations across industry verticals. Delete the stack from the AWS CloudFormation console.

Data Lake 101

Data Lake Testing Snapshot Big Data 101

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. It consists of full-day and intraday tables.

Analytics 59

Analytics Data Lake Testing Optimization 59

AWS Big Data

AUGUST 16, 2023

Conclusion In this post, we introduced a serverless CDC solution for semi-structured data using DynamoDB Streams and processing them in Iceberg tables. We demonstrated how to ingest semi-structured data in DynamoDB, identify changed data using DynamoDB Streams, and process them in Iceberg tables.

Data Lake 97

Data Lake Metadata Testing Snapshot 97

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

DECEMBER 17, 2024

DeNA selected Redshift Serverless, primarily due to its serverless nature, optimal cost-performance, and the superior processing performance for structured data typical of a data warehouse service. Kaito Tawara is a Data Engineer at DeSC Healthcare, a subsidiary of DeNA, focusing on improving healthcare data platforms.

Data Quality 91

Data Quality Testing Metrics Optimization 91