AWS Big Data

NOVEMBER 13, 2023

The upstream data pipeline is a robust system that integrates various data sources, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK) for handling clickstream events, Amazon Relational Database Service (Amazon RDS) for delta transactions, and Amazon DynamoDB for delta game-related information.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. You can’t quality-control your data integrations or reports with only some details. .

Testing 130

Testing Data-driven Visualization Dashboards 130

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Data is crucial to every organization’s survival.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 133

Data Analytics Diagnostic Analytics Management Analytics 133

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

Cloudera

JUNE 1, 2021

Our partnership with CD&R and KKR will enable us to pursue exciting new markets that offer tremendous growth opportunities. . CDP is gaining tremendous momentum in the market and the rate of adoption in our customers is at an all-time high. Said simply, Datacoral offers a fully-managed service for worry-free data integrations.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 112

Data Strategy Strategy Data Governance Marketing 112

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Alation

AUGUST 11, 2022

He now puts his 30-plus years of industry experience to work at his eponymous consulting firm , helping companies use data and analytics to discover opportunities for market advancement and growth. Data fabric, data mesh, modern data stack. Data fabric is a technology architecture. It could be gross margin.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Sisense

AUGUST 6, 2020

Integrating AI and ML into your product or service is becoming basic table stakes for staying in the market. Doing it right can mean the difference between thriving in the new world of data and disappearing from it. Know the limitations of your existing dataset and answer these questions: What categories of data are there?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Occam's Razor

OCTOBER 19, 2010

Disclosure:] I am the co-Founder of Market Motive Inc and the Analytics Evangelist for Google. None of these tools vendors have any relationship with Market Motive either. Most web analytics tools (including all the ones mentioned above) provide not great data about consumption of your website on mobile devices. Percent Mobile.

Analytics 135

Analytics Testing Measurement Optimization 135

CIO Business Intelligence

JANUARY 24, 2024

Gather/Insert data on market trends, customer behavior, inventory levels, or operational efficiency. IoT, Web Scraping, API, IDP, RPA Data Processing Data Pipelines and Analysis Layer Employ data pipelines with algorithms to filter, sort, and interpret data, transforming raw information into actionable insights.

IoT 108

IoT Machine Learning Optimization Internet of Things 108

Sisense

MAY 14, 2019

Periscope Data provides an industry-leading platform for complex analysis that allows teams to experiment with machine learning and other advanced processes to unlock new value from data. These additions make us, combined, far and away, the broadest end to end solution for every type of builder in the market. Better Together.

Data-driven 49

Data-driven Machine Learning Business Intelligence Consulting 49

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. 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

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MARCH 14, 2024

Microsoft Fabric offers a unified platform for data engineering, science, and analytics, integrating data from Power BI, Azure Synapse, and Azure Data Factory, and using open storage for accessibility and portability. It enhances analytics capabilities, streamlines migration, and enhances data integration.

Analytics 52

Analytics Management Reporting Enterprise 52