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 107

Data Warehouse Testing Data Quality Reporting 107

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 105

Data Lake Management Metrics Data Warehouse 105

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 130

Data Architecture Data Warehouse Statistics Visualization 130

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. dbt used in transformation pipelines on data warehouses (Image source: [link].

Data Warehouse 81

Data Warehouse Data Transformation Testing Data Lake 81

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. Please refer to the Microsoft documentation for detail. ” For Liftie-based data services: the entitlement “LIFTIE_AKS_DISABLE_PRIVATE_DNS_ZONE” must be set.

Data Warehouse 52

Data Warehouse Machine Learning Data Lake Management 52

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

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

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 135

Data mining Data-driven Statistics OLAP 135

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 99

Data Warehouse Testing Data Lake Data-driven 99

CDW Research Hub

JANUARY 27, 2020

Are you preparing to move data to a Snowflake data warehouse? Document the existing solution. List databases and data objects that need to be migrated. Define known data quality issues to be addressed. List processes and tools that populate and pull data from the existing solution.

Data Warehouse 52

Data Warehouse Testing Data Quality IT 52

Cloudera

APRIL 21, 2021

We started by looking at the CDP Upgrade Documentation paying particular attention to Requirements and Supported Versions and the Pre-upgrade Transition Steps , which call out the parts of the product that have changed the most. What specific components of CDP (like HBase, Impala, etc.) Life on CDP.

Testing 119

Testing Data Processing Interactive Data Warehouse 119

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

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 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

Smart Data Collective

JUNE 6, 2021

If your company revolves around the manufacturing of goods or services, for example, big data can aid you in the development of your products. This can be done through the analysis of previous product success as well as the data collected from test markets and/or social groups that may dictate what commercial offerings are best received.

Big Data 132

Big Data Data Analytics Analytics Cost-Benefit 132

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

AWS Big Data

NOVEMBER 30, 2023

This integration simplifies the authentication and authorization process for Amazon Redshift users using Query Editor V2 or Amazon Quicksight , making it easier for them to securely access your data warehouse. Note: Your organization’s IdC instance must be in the same region as the Amazon Redshift data warehouse you’re connecting to.

Data Warehouse 83

Data Warehouse Finance Sales Management 83

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

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. Please see the linked documentation to see how to take advantage of this feature.

Snapshot 70

Snapshot Metadata Data Warehouse Testing 70

Cloudera

JANUARY 19, 2024

Please refer to the product documentation for more information about specific releases. 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. or higher on the public cloud.

Data Warehouse 72

Data Warehouse Data Processing Optimization Modeling 72

Jet Global

FEBRUARY 23, 2024

This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format. Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application. Finally, test and automate your data mapping process.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse.

Analytics 65

Analytics Data Warehouse Optimization Metrics 65

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 100

Data Warehouse Snapshot Data Processing Management 100

CIO Business Intelligence

AUGUST 8, 2022

The setup primed Grant Thornton for success in those early days of the pandemic, but it was an online desktop service that Swift had been evaluating in beta testing that would prove pivotal in those trying times: enduring the tax season with a global shortage of auditors. “We Today, roughly 85% of the firm’s data is in the cloud.

Cost-Benefit 91

Cost-Benefit Digital Transformation Testing Data Warehouse 91

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. In addition, erwin DM users have the ability to: Visualize any data, from anywhere.

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

erwin

AUGUST 7, 2019

The process begins with the target or data end point, and then traversing the processes, applications, and ETL tasks in reverse from the target. The data sources that feed the ETL process are added to a “task list,” and the process is repeated for each of those sources. At each stage, the discovered pieces of lineage are documented.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

Alation

DECEMBER 21, 2022

MDM is a discipline that helps organize critical information to avoid duplication, inconsistency, and other data quality issues. Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management.

Management 52

Management Data Quality Metadata Testing 52

Insight

MAY 20, 2020

Getting started with Spark & batch processing frameworks What you need to know before diving into big data processing with Apache Spark and other frameworks. When I was an Insight Data Engineering Fellow in 2016, I knew very little about Apache Spark prior to starting the program. the older but core API?—?it’s

Data Warehouse 106

Data Warehouse Optimization Interactive Cost-Benefit 106

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

Cloudera

AUGUST 26, 2020

The Cloudera Connect Technology Certification program uses a well-documented process to test and certify our Independent Software Vendors’ (ISVs) integrations with our data platform. This allows our customers to reduce spend on highly specialized hardware and leverage the tools of a modern data warehouse. .

Machine Learning 82

Machine Learning Big Data Data Warehouse Data-driven 82

erwin

FEBRUARY 19, 2021

Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. It harvests metadata from various data sources and maps any data element from source to target and harmonize data integration across platforms.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

Machine Learning 65

Machine Learning Data Warehouse Modeling Cost-Benefit 65

Jet Global

APRIL 25, 2024

The PCAOB sets and enforces audit standards for the planning, execution, and documentation of audits; it is actively involved in setting standards and providing guidance related to internal control audits, ensuring that auditors follow established protocols and leave a clear audit trail.

Reporting 52

Reporting Risk Management Risk Software 52

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. These processes could include reports, campaigns, or financial documentation.

Data Quality 241

Data Quality Metrics Data-driven Management 241

IBM Big Data Hub

AUGUST 1, 2023

Fortunately, data stores serve as secure data repositories and enable foundation models to scale in both terms of their size and their training data. Data stores suitable for business-focused generative AI are built on an open lakehouse architecture, combining the qualities of a data lake and data warehouse.

Modeling 58

Modeling Cost-Benefit Data Lake Machine Learning 58