AWS Big Data

AUGUST 7, 2023

Many businesses use different software tools to analyze historical data and past patterns to forecast future demand and trends to make more accurate financial, marketing, and operational decisions. Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future.

Forecasting 83

Forecasting Data Warehouse Machine Learning Modeling 83

Sisense

OCTOBER 6, 2020

These programs and systems are great at generating basic visualizations like graphs and charts from static data. The challenge comes when the data becomes huge and fast-changing. Why is quantitative data important? What are the problems with quantitative data? Quantitative data is the bedrock of your BI and analytics.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

datapine

MAY 31, 2022

More and more CRM, marketing, and finance-related tools use SaaS business intelligence and technology, and even Adobe’s Creative Suite has adopted the model. We mentioned the hot debate surrounding data protection in our definitive business intelligence trends guide. It is evident that the cloud is expanding.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? That was the origin of big data. Then things changed.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

JUNE 22, 2022

After years of breakthroughs in fundamental and foundational technologies, Huawei has now brought the very first deterministic Internet Protocol (IP) network to market, dramatically minimizing network uncertainties.

Digital Transformation 101

Digital Transformation Internet of Things Manufacturing Unstructured Data 101

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Peter James Thomas

AUGUST 12, 2018

By the time that people who need to take decisions based on such information are in the loop, the inherent uncertainty of the prediction may have disappeared. Why Business Intelligence projects fail” (2009). Ideas for avoiding Big Data failures and for dealing with them if they happen (2017).

Metrics 49

Metrics Statistics Data Quality Measurement 49

Sisense

DECEMBER 13, 2021

To thrive in the age of accelerated digital, modern financial institutions need access to actionable business intelligence. It’s what allows them to unlock the full power of their data and make informed decisions. But, many don’t know where to begin or how exactly to work with their data to their optimal benefit.

Data-driven 59

Data-driven IT Business Intelligence Cost-Benefit 59

datapine

DECEMBER 28, 2021

Statistical analyses have historically been a stalwart of the high-tech and advanced business industries, and today they are more important than ever. With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market.

Statistics 363

Statistics Advertising Visualization Data mining 363