AWS Big Data

DECEMBER 19, 2024

Data has become an invaluable asset for businesses, offering critical insights to drive strategic decision-making and operational optimization. The existence of a central data catalog enabled teams to seamlessly search, discover, share, and subscribe to data assets produced within the business.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

DataKitchen

JUNE 24, 2021

Before we jump into a methodology or even a data strategy-based approach, what are we trying to accomplish? Automate the data collection and cleansing process. Tyo pointed out, “Don’t do data for data’s sake. There is no data strategy, it’s only a business strategy.”. Take a show-me approach.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI). This can help identify any discrepancies in data values or data types.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

Smarten

APRIL 19, 2024

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

Analytics 59

Analytics Predictive Modeling KPI Machine Learning 59

Ontotext

SEPTEMBER 1, 2023

LLMs in particular have remarkable capabilities to comprehend and generate human-like text by learning intricate patterns from vast volumes of training data; however, under the hood, they are just statistical approximations. Leveraging the adoption framework, this team will help ensure proper data quality, security, and compliance.

Risk 52

Risk Modeling Data Quality Data Governance 52

Jet Global

FEBRUARY 25, 2025

Data cleansing is the process of identifying and correcting errors, inconsistencies, and inaccuracies in a dataset to ensure its quality, accuracy, and reliability. This process is crucial for businesses that rely on data-driven decision-making, as poor data quality can lead to costly mistakes and inefficiencies.

Cost-Benefit 52

Cost-Benefit Data Collection Finance Reporting 52

Peter James Thomas

SEPTEMBER 19, 2018

Data Controls. Data Curation (contributor: Tenny Thomas Soman ). Data Democratisation. Data Dictionary. Data Engineering. Data Ethics. Data Integrity. Data Lineage. Data Platform. Data Strategy. Data Wrangling (contributor: Tenny Thomas Soman ).

Analytics 45

Analytics Testing Data Strategy Data Integration 45

CIO Business Intelligence

APRIL 9, 2025

If we dig deeper, we find that two factors are really at work: Causal data versus correlated data Data maturity as it relates to business outcomes. One of the most fundamental tenets of statistical methods in the last century has focused on correlation to determine causation.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

Grooper

AUGUST 19, 2019

Data science skills. Technology – i.e. data mining, predictive analytics, and statistics. Best practices for exploring collected data. Data is crucial to the success of business analytics. Just as Henry Ford used data to ensure success in the early 1900’s, we also depend on volumes of high-quality data.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54