DataKitchen

DECEMBER 9, 2022

DataOps observability involves the use of various tools and techniques to monitor the performance of data pipelines, data lakes, and other data-related infrastructure. This can include the use of tools for data integration and transformation, as well as technologies for managing and monitoring data-related systems and processes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

Wayne Yaddow

MARCH 3, 2025

These strategies minimize risks, streamline deployment processes, and future-proof data transformations, allowing businesses to trust their data before it ever reaches production. Helps maintain business rule consistency and avoid regressions in data quality overtime.

Data Quality 52

Data Quality Strategy ROI Testing 52

Sisense

AUGUST 6, 2020

This is also an important takeaway for teams seeking to implement AI successfully: Start with the key performance indicators (KPIs) you want to measure your AI app’s success with, and see where that dovetails with your expert domain knowledge. Then tailor your approach to leverage your unique data and expertise to excel in those KPI areas.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Zenia Graph’s Salesforce Accelerator makes this a reality.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

FineReport

JUNE 7, 2024

Elevate your data transformation journey with Dataiku’s comprehensive suite of solutions. Key Features Intuitive Data Visualization Tools : Tableau offers a wide range of intuitive tools that allow users to create interactive data visualization effortlessly.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

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

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

OCTOBER 28, 2021

Too much access increases the risk that data can be changed or stolen. Remove Low Quality, Unused, or “Stale” Data. In healthcare especially, data integrity is incredibly important. Low quality, unused, or “stale” data can negatively impact research by skewing findings. Monitor, Measure, and Continuously Improve.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

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 Science Data Transformation 52

Occam's Razor

OCTOBER 19, 2010

You'll measure Task Completion Rate in 4Q (below). You'll measure Share of Search using Insights for Search (below). Only a plea to obsessively obsess about measuring outcomes and compute economic value, not just revenue. We are faced with new marketing and measurement challenges and opportunities every single day.

Analytics 136

Analytics Testing Measurement Optimization 136

Jet Global

AUGUST 24, 2023

Data Security Concerns: Managing data security and compliance across hybrid environments can be a significant concern. Financial data is sensitive and requires robust security measures. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system.

Finance 52

Finance Reporting Data Integration Data Warehouse 52

Jet Global

MAY 1, 2023

Manage compliance through up-to-the-minute performance measures, workflow automation, and essential regulatory reports. Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. Data Transformation and Enrichment Data can be enriched for analysis. How to measure the value.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

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 118

IoT Machine Learning Internet of Things Optimization 118

DataKitchen

JANUARY 23, 2023

Testing data and analytic systems require a development system with accurate test data, tools, and relevant tool code. Only then can you tell the true impact of a column name change on the data transformations, the models, and the visualization you give to your customers. They measure data sets at a point in time.

Testing 130

Testing Data Governance Data Quality Data-driven 130