Smarten

JUNE 29, 2018

This article focuses on the Independent Samples T Test technique of Hypothesis testing. What is the Independent Samples T Test Method of Hypothesis Testing? Let’s look at a sample of the Independent t-test on two variables. How Can the Independent Samples T Test Method Benefit an Organization? About Smarten.

Testing 40

Testing Statistics IT Business Intelligence 40

Smarten

JUNE 26, 2018

This article describes chi square test of association and hypothesis testing. What is the Chi Square Test of Association Method of Hypothesis Testing? Let’s conduct the Chi square test of independence using two variables: Gender and Product category. Use Case – 1. About Smarten.

Testing 40

Testing Statistics IT Business Intelligence 40

Smarten

JUNE 29, 2018

This article discusses the Paired Sample T Test method of hypothesis testing and analysis. What is the Paired Sample T Test? The Paired Sample T Test is used to determine whether the mean of a dependent variable e.g., weight, anxiety level, salary, reaction time, etc., is the same in two related groups.

Business Analysis 40

Business Analysis Testing Statistics Advertising 40

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 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

Smarten

JUNE 17, 2022

After completion of the testing procedure, the certificate is provided to show that all requirements were met. The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

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 25, 2019

Augmented analytics allows for data prep, Smart Data Visualization and Assisted Predictive Modeling with the help of machine learning and natural language processing (NLP), so users need not be trained as data scientists to get to the heart of the data and find those elusive nuggets of information that will help them create, change and improve.

Analytics 51

Analytics Predictive Modeling Visualization Machine Learning 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

BizAcuity

APRIL 1, 2023

There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. Exploratory Data Analysis (EDA) EDA is used to analyze data and summarize their main properties and characteristics using visual techniques.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

O'Reilly on Data

DECEMBER 12, 2019

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. 6] Debugging may focus on a variety of failure modes (i.e.,

Machine Learning 192

Machine Learning Modeling Testing Risk Management 192

Smart Data Collective

SEPTEMBER 17, 2020

Nowadays, terms like ‘Data Analytics,’ ‘Data Visualization,’ and ‘Big Data’ have become quite popular. Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. In this modern age, each business entity is driven by data. The Role of Big Data.

Big Data 140

Big Data Finance Risk Management Risk 140

BizAcuity

JANUARY 18, 2023

There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. Predictive modeling for flagging suspicious activity. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smarten

NOVEMBER 8, 2022

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Business Intelligence 52

Business Intelligence Predictive Modeling Statistics Data-driven 52

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. The 12-week data management course covers Python, data quality, data visualization, GDRP, and database management.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

AUGUST 23, 2023

“You’re able to select a smaller number of stocks with predictive return and lower operational and transaction costs, which ultimately means that you can reduce the variability and more accurately predict returns,” Muthukrishnan says. It’s important for us to test the technology and be ready,” Muthukrishnan says.

IT 97

IT Machine Learning Risk Optimization 97

Juice Analytics

MARCH 11, 2021

3) That’s where our data visualization and user experience capabilities helped them turn this data into a web-based analytical tool that focused users on the metrics and peer groups they cared about. There are many paths to consider: Visual representations that reveal patterns in the data and make it more human readable. Just kidding!

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

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.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

Smarten

JANUARY 8, 2019

Augmented Analytics advantages support users by empowering them and encouraging user adoption with auto-recommendations and suggestions that help them visualize data in a way that makes sense for the type of data they are analyzing. Empower users with augmented analytics that include ETL for business users, smart data visualization and more!

Analytics 40

Analytics Predictive Modeling Visualization Business Analysis 40

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

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. It’s also necessary to understand data cleaning and processing techniques.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. What is Data in Use?

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

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

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. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 89

Cost-Benefit Insurance Unstructured Data Machine Learning 89

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

Birst BI

OCTOBER 30, 2018

The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Integrate the data sources of the various behavioral attributes into a functional data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

JUNE 27, 2018

When a business uses Outlier analysis, it is important to test the results and analyze the overall dataset and environment to be sure that the presence of outliers does not indicate that the dataset may be more complex than anticipated and may require a different form of analysis.

IT 40

IT Business Intelligence Predictive Modeling Testing 40

Smarten

JUNE 25, 2018

Business Problem: Discount Analysis and Customer Retention will help the organization to target discounts to specific customers and the business will need to visualize ‘segments of sales group based on discount behavior’ and ‘customer churn to identify segments of customers on the verge of leaving’. Use Case – 2.

Enterprise 40

Enterprise IT Business Intelligence Predictive Modeling 40

Smarten

JUNE 20, 2018

The business can use this information for forecasting and planning, and to test theories and strategies. The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

JUNE 29, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Enterprise 40

Enterprise IT Statistics Business Intelligence 40

Smarten

JUNE 29, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Enterprise 40

Enterprise Sales Statistics Business Intelligence 40

Smarten

JUNE 28, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

IT 40

IT Business Intelligence Predictive Modeling Risk 40

Smarten

JUNE 29, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Forecasting 40

Forecasting Enterprise IT Business Intelligence 40

Smarten

JUNE 29, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Business Analysis 40

Business Analysis IT Sales Statistics 40

Smarten

JUNE 26, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Forecasting 40

Forecasting Enterprise IT Sales 40

Smarten

JUNE 29, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 29, 2018

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Business Analysis 40

Business Analysis IT Measurement Statistics 40