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 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

Smarten

AUGUST 21, 2019

Using the Smarten approach, users can quickly and easily prepare and analyze data and visualize and explore data, notate and highlight data and share data with others. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

Smarten

JUNE 10, 2022

Data Discovery including self-serve data preparation, smart data visualization with charts, graphs and other visualizations for clarity and decisions. Predictive Modeling to support business needs, forecast, and test theories. Assisted Predictive Modeling. Smart Data Visualization.

Slice and Dice 52

Slice and Dice Analytics Key Performance Indicator Business Intelligence 52

Smarten

JANUARY 31, 2019

Put simply, business Intelligence uses historical data to reveal where the business has been, and managers can use this data to predict competitive response and discover what is changing in customer buying behavior and in sales. How is Advanced Analytics Different from Business Intelligence?

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

IBM Big Data Hub

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. An e-commerce conglomeration uses predictive analytics in its recommendation engine.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

IBM Big Data Hub

FEBRUARY 14, 2024

Creative AI use cases Create with generative AI Generative AI tools such as ChatGPT, Bard and DeepAI rely on limited memory AI capabilities to predict the next word, phrase or visual element within the content it’s generating. Maintenance schedules can use AI-powered predictive analytics to create greater efficiencies.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

Smarten

JUNE 20, 2018

The business can use this information for forecasting and planning, and to test theories and strategies. For example, the decision to the ARIMA or Holt-Winter time series forecasting method for a particular dataset will depend on the trends and patterns within that dataset.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

NOVEMBER 3, 2017

Business users can quickly and easily prepare and analyze data and visualize and explore data, notate and highlight data and share data with others to identify the important ‘nuggets’, buried in traditional data, and to connect the dots, find exceptions, identify patterns and trends and better predict results.

Analytics 40

Analytics Visualization Experimentation Cost-Benefit 40

Birst BI

AUGUST 23, 2018

Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. Develop and test a model in R Studio. Assess and validate the model with analysts and business users. Connect R Studio to a cleaned dataset in Birst.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Smarten

JUNE 29, 2018

Multiple linear regression models are useful in helping an enterprise to consider the impact of multiple independent predictors and variables on a dependent variable, and can be beneficial for forecasting and predicting results. About Smarten.

Business Analysis 40

Business Analysis IT Sales Statistics 40

Smarten

JUNE 29, 2018

Weather Forecasting – Based on temperature, humidity, pressure etc., an organization can predict if it will be rainy/sunny/windy tomorrow. a business can predict the likelihood of fraud. It is useful for making predictions and forecasting data based on historical results. About Smarten.

Enterprise 40

Enterprise IT Business Intelligence Forecasting 40

Smarten

JUNE 27, 2018

SVM Classification Analysis can be used for many analytical tasks: Credit/Loan Approval Analysis – Given a list of client transactional attributes, a business can predict whether a client will default on a loan. Medical Diagnosis – Given a list of symptoms, a doctor can predict if a patient has a particular disease.

Business Analytics 40

Business Analytics Analytics IT Business Intelligence 40

Smarten

JUNE 29, 2018

The KNN Classification algorithm is useful in determining probable outcome and results and in forecasting and predicting results, given the existence of multiple variables. About Smarten.

Enterprise 40

Enterprise Business Intelligence Predictive Modeling Statistics 40

Smarten

JULY 10, 2018

Use Case(s): Weather Forecasting, Fraud Analysis and more. Independent Samples T Test: What is the Independent Samples T Test Method of Analysis and How Can it Benefit an Organization? Paired Sample T Test: What is the Paired Sample T Test and How is it Beneficial to Business Analysis?

Analytics 40

Analytics Forecasting Statistics Sales 40

Rocket-Powered Data Science

SEPTEMBER 20, 2021

The data scientists need to find the right data as inputs for their models — they also need a place to write-back the outputs of their models to the data repository for other users to access. The BI team may be focused on KPIs, forecasts, trends, and decision-support insights. That’s data democratization.

Data Science 285

Data Science Forecasting Business Intelligence Sales 285

DataRobot Blog

JUNE 24, 2022

In addition, traditional analytical approaches are not flexible enough in generating alternative scenarios that allow investment analysts to test market shifts or to compare predictive-model outputs to the forecasts of traditional sources of market information. Forecasting the Real Estate Market Using DataRobot.

Forecasting 52

Forecasting Machine Learning Marketing Data-driven 52

Cloudera

JANUARY 25, 2022

As roles within organizations evolve (as seen by the growth of citizen scientists and analytics engineers) and as data needs change (think schema changes and real-time), we need more intelligent ways to perform visual exploration, data interrogation, and share insights. Figure: Launch screen of the Flight Prediction AMP.

Visualization 88

Visualization Machine Learning Predictive Analytics Data-driven 88

Domino Data Lab

AUGUST 22, 2019

GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper. This test set is available at download.tensorflow.org/data/questions-words.txt.].

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Smarten

JANUARY 24, 2019

With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as business users leverage systems and solutions that are designed with Machine Learning capabilities to predict outcomes and analyze data.

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

Smarten

JULY 3, 2017

When an enterprise selects a self-serve business intelligence solution with Advanced Data Discovery , Smart Data Visualization , Plug n’ Play Predictive Analysis and Self-Serve Data Preparation , it can create an environment where business users are empowered and become greater assets to the organization. It’s simple!

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2) Data Discovery/Visualization. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

DECEMBER 3, 2023

So, you can ask, ‘Who sold the most bakery items in the Southwest region from September through November of 2022,’ and you will receive your results and can visualize your data in a way that makes sense to you and to your team. What is self-service analytics? We should probably explain before we move on.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. What is the Holt-Winters Forecasting Algorithm? The Holt-Winters algorithm is used for forecasting and It is a time-series forecasting method. 2) Double Exponential Smoothing Use Case.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Smarten

MAY 2, 2019

An Advanced Analytics Platform should include self-serve data preparation, smart data visualization and assisted predictive modeling with natural language processing and machine learning that will support users with simple search analytics.

Analytics 0

Analytics Predictive Analytics Predictive Modeling Forecasting 0

Jet Global

MAY 1, 2023

Healthcare is forecasted for significant growth in the near future. 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

Jet Global

SEPTEMBER 1, 2023

Data-Driven Decision Making: Embedded predictive analytics empowers the development team to make informed decisions based on data insights. By integrating predictive models directly into the application, developers can provide real-time recommendations, forecasts, or insights to end-users.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52