CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 135

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 135

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. As the foundation for ChatGPT and other developed solutions, GPT can be used for a wide range of tasks and is well-suited for language translation and content creation (as opposed to content repurposing).

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Smarten

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Machine Learning and Predictive Modeling of Customer Churn. Building Your Churn Model. segmentation on steroids).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Examples include credit card fraud monitoring solutions used by banks, or tools used to optimize the placement of wind turbines in wind farms. What is data science?

Data Science 139

Data Science Statistics Machine Learning Visualization 139

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. The models are then used to spot errors and suggest the “most probable” values to replace.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

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 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

The Unofficial Google Data Science Blog

JANUARY 31, 2017

By OMKAR MURALIDHARAN, NIALL CARDIN, TODD PHILLIPS, AMIR NAJMI Given recent advances and interest in machine learning, those of us with traditional statistical training have had occasion to ponder the similarities and differences between the fields. Some branches of machine learning (e.g.

Machine Learning 73

Machine Learning Modeling Statistics Predictive Modeling 73

CIO Business Intelligence

MAY 9, 2024

At a high level, a CAIO will need to understand the business well enough to identify where AI can make an impact, whether through new value streams or optimization, Daly says. And they should have a proficiency in data science and analytics to effectively leverage data-driven insights and develop AI models.

Risk Management 129

Risk Management Risk Cost-Benefit Technology 129

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

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 Recreation/Entertainment Predictive Analytics 110

DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. The accuracy of machine learning models is highly dependent on the quality of the training data.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Smarten

MARCH 13, 2024

Self-Serve Data Preparation Assisted Predictive Modeling Smart Data Visualization Machine Learning and Natural Language Processing (NLP) Clickless Search Analytics EXPECTATIONS AND RESULTS Once you have chosen the right augmented analytics solution, you must establish appropriate expectations.

Analytics 52

Analytics Predictive Modeling Strategy Enterprise 52

CIO Business Intelligence

JULY 26, 2023

And the crew is using AWS SageMaker machine learning (ML) to give its agents the best local leads and prospective buyers. But Cox and Djuric do know that 82% of Keller Williams’ agent have been active on the homegrown CRM application in the past 90 days and can deduce the high value of their data from that statistic alone.

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

DataRobot

JANUARY 13, 2022

Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. It offers a visual and intuitive UI that enables anyone to explore and prepare data for machine learning, no matter their previous machine-learning experience.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Smarten

AUGUST 21, 2019

Assisted Predictive Modeling – These tools enable the average business user to leverage sophisticated predictive algorithms without requiring statistical or data science skills. ” There are many features and benefits to the Smarten approach to Advanced Data Discovery.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

Smarten

DECEMBER 17, 2018

Tools like Assisted Predictive Modeling allow the average business user to become a Citizen Data Scientist with tools that offer guidance and auto-suggestions to help the user arrive at the outcome they need without being frustrated or having to call in an army of analysts and IT staff to help them complete their analysis.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Statistics 40

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Birst BI

AUGUST 23, 2018

A key goal of AI or machine learning automation is to have machines complete tasks for you, freeing up time so you can focus on the more complex, higher-value tasks. 1] Until then, we observe in another Gartner survey that organizations are outsourcing various tasks in the Machine Learning pipeline. [2].

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 83

Machine Learning Modeling Deep Learning Predictive Modeling 83

BI-Survey

JANUARY 29, 2023

For many organizations, modern technology around machine learning (ML) and the cloud, as well as its growing ease of use, offer a great opportunity for optimization. Specialized planning solutions, which form the backbone of corporate planning in many organizations, are rarely used for predictive planning.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

BI-Survey

MARCH 16, 2021

Companies consider the improvement of the software they use (56 percent) to be the most important investment for optimizing planning and forecasting. To achieve this, many organizations strive for a more intensive use of predictive algorithms, statistical methods and machine learning (ML) models.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

MARCH 16, 2021

Companies consider the improvement of the software they use (56 percent) to be the most important investment for optimizing planning and forecasting. To achieve this, many organizations strive for a more intensive use of predictive algorithms, statistical methods and machine learning (ML) models.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

Smarten

OCTOBER 9, 2018

The benefits of augmented analytics and, specifically, of predictive analytics and assisted predictive modeling , are numerous, so there are plenty of reasons to embrace this approach and plenty of advantages of advanced analytics. Business users can analyze, share and optimize business potential. That is a true benefit!

Predictive Analytics 40

Predictive Analytics Analytics Predictive Modeling Forecasting 40

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Predictive models indicate that the machine learning market will grow at a compound annual growth rate (CAGR) of 38.8%

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Predictive models indicate that the machine learning market will grow at a compound annual growth rate (CAGR) of 38.8%

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

MARCH 23, 2021

On top of this, pre-existing societal biases are being reinforced and promulgated at previously unheard of scales as we increasingly integrate machine learning models into our daily lives. Put simply, we are reduced to the inputs of an algorithm.

Internet Publishing and Broadcasting 317

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 317

DataRobot Blog

DECEMBER 1, 2022

You may learn that customers who were grouped together using a traditional approach to market segmenting look very different after a machine learning assisted analysis. As you upload your data, DataRobot will do some initial exploratory data analysis to get a deeper understanding of the dataset prior to model training.

Machine Learning 52

Machine Learning Marketing Modeling Statistics 52

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] With the SG architecture, context words are predicted given the target word. With CBOW, it is the inverse: The target word is predicted based on the context words. Journal of Machine Learning Research, 9, 2579–605.]. Example 11.6

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Cloudera

NOVEMBER 2, 2020

the time it takes for the data to be optimally queryable is faster – query immediately upon arrival with no need for processing or aggregation or compaction. Optimized for insert only as well as insert+update patterns. Optimized for point lookups, analytics, mutations, etc. with low latency and high concurrency.

Data Warehouse 94

Data Warehouse Optimization Dashboards Interactive 94

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. Prescriptive analytics goes a step further into the future.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

Without a doubt, it’s a big technological advancement, and one of the big statistics buzzwords, but the extent to which it is believed to be already applied is vastly exaggerated. The commercial use of predictive analytics is a relatively new thing. The accuracy of the predictions depends on the data used to create the model.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. Meanwhile, predictive analytics enable them to analyze customer market trends.

Data Analytics 52

Data Analytics Analytics ROI Data Governance 52

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. Meanwhile, predictive analytics enable them to analyze customer market trends.

Data Analytics 40

Data Analytics Analytics ROI Data Governance 40