Sisense

MARCH 19, 2019

To extract the maximum value from your data, it needs to be accessible, well-sorted, and easy to manipulate and store. Amazon’s Redshift data warehouse tools offer such a blend of features, but even so, it’s important to understand what it brings to the table before making a decision to integrate the system.

Data Warehouse 94

Data Warehouse Cost-Benefit Business Intelligence Data Processing 94

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 76

Data Warehouse Sales Visualization Data Processing 76

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g.,

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Complete the implementation tasks such as data ingestion and performance testing.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

O'Reilly on Data

FEBRUARY 19, 2021

The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. A Wave of Cloud-Native, Distributed Data Frameworks.

Data Lake 289

Data Lake Data Warehouse Machine Learning Modeling 289

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 93

Data Lake Data Warehouse Testing Business Objectives 93

AWS Big Data

NOVEMBER 17, 2023

dbt (DataBuildTool) offers this mechanism by introducing a well-structured framework for data analysis, transformation and orchestration. It also applies general software engineering principles like integrating with git repositories, setting up DRYer code, adding functional test cases, and including external libraries. project-dir.

Snapshot 87

Snapshot Data Processing Testing Data Warehouse 87

AWS Big Data

MARCH 16, 2023

Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Together with price-performance , Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

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 131

Data Architecture Data Warehouse Statistics Visualization 131

AWS Big Data

NOVEMBER 9, 2023

A modern data platform entails maintaining data across multiple layers, targeting diverse platform capabilities like high performance, ease of development, cost-effectiveness, and DataOps features such as CI/CD, lineage, and unit testing. local/bin/dbt test –-select your_package.* /usr/local/airflow/.local/bin/dbt

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

DataKitchen

JANUARY 19, 2022

Imagine a large enterprise yielding significant value from their Matillion-Snowflake integration, but wishing to expand the scope of data pipeline deployment, testing, and monitoring. DataKitchen triggers a Matillion job, then retrieves execution parameters that can be used in DataKitchen tests.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 95

Data Warehouse Testing Data Lake Data-driven 95

CIO Business Intelligence

MARCH 29, 2024

One of the most valuable aspects of AWS Bedrock, Woodring says, is that it establishes a standard data platform for Rocket, which will enable the mortgage lender to get its data “very quickly” to the right AI model. In other cases, Rocket will test out various AI models and “see their efficacy in different tasks,” Woodring says.

Data Lake 124

Data Lake Machine Learning Data Warehouse Unstructured Data 124

CIO Business Intelligence

OCTOBER 26, 2023

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 127

Business Intelligence Data-driven Statistics Data Warehouse 127

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

DataKitchen

AUGUST 27, 2021

They mastered hundreds of data sets, serving thousands of people, with very few errors or missed SLAs (service level agreements). The Otezla team built a system with tens of thousands of automated tests checking data and analytics quality. Has the data arrived on time? Is the quantity of data correct?

Analytics 246

Analytics Sales Testing Cost-Benefit 246

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. The organizational concepts behind data mesh are summarized as follows.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

DataKitchen

OCTOBER 5, 2021

Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires. Create tests. Run the factory.

Testing 157

Testing Dashboards Measurement Experimentation 157

IBM Big Data Hub

NOVEMBER 6, 2023

To ensure uptake of products, service providers must have the appropriate tech tools to help SMBs understand the value of these products and to help with testing and implementation. Generative AI can turn SMB needs into product use cases, and the appropriate tech systems can allow SMBs to test products in a sandbox.

Cost-Benefit 109

Cost-Benefit Enterprise ROI Data Warehouse 109

DataKitchen

NOVEMBER 4, 2021

These limited-term databases can be generated as needed from automated recipes (orchestrated pipelines and qualification tests) stored and managed within the process hub. . The process hub capability of the DataKitchen Platform ensures that those processes that act upon data – the tests, the recipes – are shareable and manageable.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

DataKitchen

JANUARY 3, 2022

There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. DataOps expands upon this approach by focusing on the processes and workflows that create data enablement and business analytics. DataOps Process Hub. Stop Firefighting.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

AWS Big Data

AUGUST 31, 2023

One of the major and essential parts in a data warehouse is the extract, transform, and load (ETL) process which extracts the data from different sources, applies business rules and aggregations and then makes the transformed data available for the business users.

Data Warehouse 79

Data Warehouse Data-driven Testing Business Intelligence 79

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. To get started, we need an Amazon Redshift Serverless data warehouse with the Redshift ML feature enabled and an Amazon SageMaker Studio environment with access to SageMaker Feature Store.

Modeling 62

Modeling Data Warehouse Machine Learning Testing 62

Paul Blogs on BI

SEPTEMBER 8, 2021

Well firstly, if the main data warehouses, repositories, or application databases that BusinessObjects accesses are on premise, it makes no sense to move BusinessObjects to the cloud until you move its data sources to the cloud. The software is exactly the same and will remain that way for the foreseeable future.

Data Warehouse 59

Data Warehouse Data Processing Data Lake Testing 59

CIO Business Intelligence

SEPTEMBER 12, 2022

Collectively, the agencies also have pilots up and running to test electric buses and IoT sensors scattered throughout the transportation system. Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. We didn’t care about what the data was,” he says. “I

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

Cloudera

FEBRUARY 12, 2024

In this blog, we’ll take you through our tried and tested best practices for setting up your DNS for use with Cloudera on Azure. For data warehouse: create data warehouses through the Cloudera command line interface with the parameter “privateDNSZoneAKS”: set to”None.”

Data Warehouse 52

Data Warehouse Machine Learning Data Lake Management 52

Cloudera

JANUARY 19, 2024

Cloudera has been testing with GPT running in both Azure and OpenAI, but the following service-model combinations are also supported: Note: Cloudera recommends using the Hue AI assistant with the Azure OpenAI service. Log in to the Cloudera Data Warehouse service as DWAdmin. Log in to the data warehouse service as DWAdmin.

Data Warehouse 72

Data Warehouse Data Processing Optimization Modeling 72

erwin

SEPTEMBER 26, 2019

So Seriously … You Should Automate Your Data Vault. Data Vault is a methodology for architecting and managing data warehouses in complex data environments where new data types and structures are constantly introduced. By Danny Sandwell.

Data Warehouse 108

Data Warehouse Cost-Benefit Data Integration Modeling 108

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

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

Data Processing 89

Data Processing Data Lake Data Warehouse Optimization 89

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Validate and test through the entire migration.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

Cloudera

JANUARY 27, 2021

The SOC 2 certification helps ensure that applications and code are developed, reviewed, tested, and released following the AICPA Trust Services Principles. Completion of internal and external penetration testing. Data backup and disaster recovery. Access control that follows “least privilege” best practices. What’s Next?

Testing 102

Testing Data Warehouse Machine Learning Measurement 102

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse). Apache Hive.

Metrics 84

Metrics Slice and Dice Data Warehouse Dashboards 84

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 134

Analytics Data Science Unstructured Data Data mining 134

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. Learn More, Keep in Touch.

Data Warehouse 93

Data Warehouse Machine Learning Visualization Data Lake 93