Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 131

Predictive Analytics Analytics Predictive Modeling Data mining 131

CIO Business Intelligence

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization. The exam consists of 40 questions and the candidate has 120 minutes to complete it.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

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. On-site courses are available in Munich. Remote courses are also available. Switchup rating: 5.0 (out

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

Domino Data Lab

JANUARY 21, 2021

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. Each dataset has properties that warrant producing specific statistics or charts.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

Data Science 101

JUNE 10, 2019

They can clean large amounts of data, explore data sets to find trends, build predictive models, and create a story around their findings. Data analysts sift through data and provide helpful reports and visualizations. A data scientist can run a project from end-to-end. Data Analysts. Step 4: Explore the data.

Data Science 96

Data Science Statistics Predictive Modeling Machine Learning 96

O'Reilly on Data

DECEMBER 12, 2019

If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. Small residuals usually mean a model is right, and large residuals usually mean a model is wrong. Interpretable ML models and explainable ML.

Machine Learning 196

Machine Learning Modeling Testing Risk Management 196

FineReport

APRIL 24, 2024

What is Data Visualization Understanding the Concept Data visualization, in simple terms, refers to the presentation of data in a visual format. By utilizing visual elements, data visualization allows individuals to grasp difficult concepts or identify new patterns within the data.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

Smarten

NOVEMBER 23, 2023

The Smarten Augmented Analytics suite includes Smart Data Visualization , AI and Assisted Predictive Modeling , Self-Serve Data Preparation , Natural Language Processing (NLP) and Search Analytics , SnapShot Monitoring and Alerts , and many other sophisticated features.

Publishing 62

Publishing Marketing Analytics Predictive Modeling 62

CIO Business Intelligence

MAY 9, 2024

And they should have a proficiency in data science and analytics to effectively leverage data-driven insights and develop AI models. This includes skills in statistical analysis, data visualization, and predictive modeling. That helps them ensure that AI initiatives adhere to legal and ethical standards.

Risk Management 138

Risk Management Risk Cost-Benefit Technology 138

FineReport

MAY 29, 2020

Business Intelligence is commonly divided into four different types: reporting, analysis, monitoring, and prediction. Static reports cannot be changed by the end-users, while interactive reports allow you to navigate the report through various hierarchies and visualization elements. The ‘data’ part is the statistics and data display.

Reporting 94

Reporting OLAP Visualization Business Intelligence 94

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. It’s quite popular for its visualizations: charts, graphs, pictures, and various plots. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smarten

NOVEMBER 26, 2024

The business can harness the power of statistics and machine learning to uncover those crucial nuggets of information that drive effective decision, and to improve the overall quality of data. This helps you select the predictors that have the greatest impact, making it easier to create an effective predictive model.

Data Quality 62

Data Quality Machine Learning Predictive Modeling Metadata 62

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

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

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Descriptive Statistics. Access to Flexible, Intuitive Predictive Modeling. Trends and Patterns. Forecasting.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Smarten

OCTOBER 25, 2017

Advanced Data Discovery allows business users to quickly and easily prepare and analyze data and visualize and explore data. And, the best part is that a business user with average skills can do all of this without specialized skills, knowledge of statistical analysis or support from IT or professional data scientists.

Predictive Modeling 63

Predictive Modeling Statistics Visualization Business Analytics 63

The Data Visualisation Catalogue

APRIL 4, 2019

I’ve implemented DataView in my own work and find it an excellent way to organize investment information, do data discovery and create predictive models. Application #2: Creating and visualizing multi-variable relationships, which is particularly useful in creating predictive models.

Dashboards 74

Dashboards Predictive Modeling Visualization Modeling 74

Smarten

APRIL 25, 2024

Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Domino Data Lab

AUGUST 12, 2021

In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase. It enables us to build context around the data at hand and lets us develop appropriate models that then can be interpreted correctly. The purpose of Data Exploration.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Smarten

JANUARY 27, 2023

Smarten has announced the launch of Predictive Model Mark-Up Language (PMML) Integration capability for its Smarten Augmented Analytics suite of products. Simply create the predictive model, using your favorite platform, export the model as a PMML file and import that model to Smarten.

Predictive Modeling 52

Predictive Modeling Analytics Predictive Analytics Business Intelligence 52

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

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. BA primarily predicts what will happen in the future. What About “Business Intelligence”?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Smarten

JUNE 17, 2022

Smarten Augmented Analytics tools include Assisted Predictive Modeling , Smart Data Visualization , Self-Serve Data Preparation , Sentiment Analysis , and Clickless Analytics with natural language processing (NLP) for search analytics.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

Jedox

MAY 17, 2022

Financial planners , Chief Financial Officers, and analysts have all struggled to build accurate methods for predicting what’s likely to happen. Prior to the dawn of advanced statistical analysis and machine learning, predictive analytics efforts fell into 4 broad categories: Guessing , which is the default that most people revert to.

Predictive Analytics 85

Predictive Analytics Finance Analytics Forecasting 85

Birst BI

OCTOBER 30, 2018

The foundation of predictive analytics is based on probabilities. To generate accurate probabilities of future behavior, predictive analytics combine historical data from any number of applications with statistical algorithms. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

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 57

Analytics Predictive Modeling KPI Machine Learning 57

Smarten

APRIL 12, 2023

Smarten Augmented Analytics tools include Assisted Predictive Modeling , Smart Data Visualization , Self-Serve Data Preparation , Sentiment Analysis , and Clickless Analytics with natural language processing (NLP) for search analytics.

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

AWS Big Data

AUGUST 21, 2024

Solution overview The AI-powered scaling and optimization feature in Redshift Serverless provides a user-friendly visual slider to set your desired balance between price and performance. The expected data scan is predicted by machine learning (ML) models based on prior historical run statistics.

Optimization 105

Optimization Data Lake Data Warehouse Cost-Benefit 105

BizAcuity

APRIL 1, 2023

Exploratory Data Analysis (EDA) EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. Predictive Analytics It is a subset of business analytics that uses statistical techniques (algorithms) to find patterns in historical data points and predict future outcomes with high accuracy.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. Widely used to discover trends, patterns, check assumptions and spot anomalies or outliers, EDA involves a variety of techniques including statistical analysis, and machine learning to gain a better understanding of data.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve. appeared first on IBM Blog.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Ms SQL Girl

MAY 19, 2016

To simplify, “In-database Advanced Analytics”: you can run powerful statistical / predictive modelling (from R) inside SQL Server. R Tools for Visual Studio : tools for developing R script in Visual Studio. R Tools for Visual Studio : tools for developing R script in Visual Studio.

Visualization 45

Visualization Predictive Modeling Statistics Reporting 45

Smarten

NOVEMBER 8, 2022

Smarten Augmented Analytics tools include Assisted Predictive Modeling , Smart Data Visualization , Self-Serve Data Preparation , Sentiment Analysis , and Clickless Analytics with natural language processing (NLP) for search analytics.

Business Intelligence 52

Business Intelligence Predictive Modeling Statistics Data-driven 52

Cloudera

NOVEMBER 2, 2020

alert when threshold exceeded over a rolling window of statistics on the data, score the event data against a predictive model to decide which action to take next). Tool for visualizing, dashboarding, and report building. This could be done for stream processing (e.g. SQL editor for running Hive and Impala queries.

Data Warehouse 102

Data Warehouse Optimization Dashboards Interactive 102

Smarten

JUNE 29, 2018

The independent sample t-test is a statistical method of hypothesis testing that determines whether there is a statistically significant difference between the means of two independent samples. This article focuses on the Independent Samples T Test technique of Hypothesis testing. About Smarten.

Testing 40

Testing Statistics IT Business Intelligence 40

Birst BI

AUGUST 23, 2018

Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. Our recruits come from various disciplines – chemistry, physics, math, statistics, operations research, and economics.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73