Birst BI

OCTOBER 30, 2018

Today, the most common usage of business intelligence is for the production of descriptive analytics. . Descriptive Analytics: Valuable but limited insights into historical behavior. The vast majority of financial services companies use the data within their applications for what is called “ Descriptive Analytics.”

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Smart Data Collective

DECEMBER 19, 2021

Both the individuals and companies that are into cryptocurrency need essential analytics that would help them to take the right decision about the market. Developers can make systems busting Python Cryptocurrency libraries that visualize best pricing schemes analyzing the market. Python Makes Decision Making Simple.

Optimization 141

Optimization Machine Learning Data mining Statistics 141

Domino Data Lab

JANUARY 21, 2021

It’s worth noting that there is a landscape of proprietary tools dedicated to producing descriptive analytics in the name of business intelligence. On the other hand, some researchers may say the emphasis on visualizing such results is unnecessary, a la, “If you know what you’re looking for, pandas.describe() is all you need”.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Sisense

SEPTEMBER 12, 2019

Most companies find themselves in the bottom left corner, in the Descriptive Analytics and Diagnostic Analytics sections. You likely already have some form of scheduled reports, are drilling down into your data, discovering what is in your data, and may even be visualizing to some extent.

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

Business Over Broadway

MARCH 13, 2019

IBM Watson Studio is an end-to-end analytics solution to help you gain insights from your data. Watson Studio accomplished this feat by providing a platform to help you prepare data and build models on your own desktop using their easy-to-use visual drag and drop tools. Case Study: The Survey Data. The next step is to analyze the data.

Statistics 78

Statistics Measurement Descriptive Analytics Machine Learning 78

Smarten

NOVEMBER 26, 2023

You may be interested to know that TechJury reports seven out of ten businesses rate data discovery as very important, and that the top three business intelligence trends are data visualization, data quality management and self-service business intelligence. or What is happening? And that is exactly what is happening!

Marketing 40

Marketing Business Intelligence Key Performance Indicator Prescriptive Analytics 40

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

Statistics 52

Statistics Data mining Visualization Reporting 52

FineReport

APRIL 26, 2023

The Big Data ecosystem is rapidly evolving, offering various analytical approaches to support different functions within a business. Descriptive Analytics is used to determine “what happened and why.” ” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

BizAcuity

MARCH 31, 2022

Artificial Intelligence Analytics. AI can be applies to all 3 major types of analytics: Descriptive Analytics: The entire journey of the descriptive and diagnostic analytics process includes data extraction, data aggregation and data mining; 3 applications where AI is widely used to reduce costs, and eliminate complex actions.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Grooper

AUGUST 19, 2019

For simple reporting projects, I might spend 8 hours getting the right data and then just a couple of hours producing the needed visualizations. Once we have right data, we do some descriptive analytics which tells us column’s mean, median, mode, standard deviation, variance, bias, some skewness – how the data is spread.

Machine Learning 40

Machine Learning Metrics Descriptive Analytics Testing 40

Domino Data Lab

JUNE 2, 2019

Her talk addressed career paths for people in data science going into specialized roles, such as data visualization engineers, algorithm engineers, and so on. In an organization the size of Netflix, teams need to be differentiated. I’m generally averse to overly-specialized job titles – given how our field is based on interdisciplinary work.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

datapine

JANUARY 31, 2022

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Jet Global

MAY 1, 2023

Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Plus, there is an expectation that tools be visually appealing to boot. In the past, data visualizations were a powerful way to differentiate a software application. Their dashboards were visually stunning. It’s all about context.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52