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 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

Smarten

DECEMBER 17, 2018

My business users don’t have the skill, the patience or the time to become data scientists. But, they don’t have to be data scientists to use augmented analytics. With these tools, users can explore patterns in data and receive suggestions to help them gain insight on their own without dependence on IT or data scientists.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Statistics 40

Smarten

AUGUST 21, 2019

Smart Data Visualization – Smart Data Visualization gives users a helping hand with suggestions and recommendations for the best possible visualization of underlying data to generate meaningful insights from data.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

Birst BI

AUGUST 23, 2018

What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases? Automating data science tasks leaves room to build more AI applications with the same amount of data science resources. Source: Gartner (April 2018).

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

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. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167

Analytics Machine Learning Data Science Deep Learning 167

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

Machine Learning 80

Machine Learning Modeling Deep Learning Predictive Modeling 80

BI-Survey

JANUARY 29, 2023

Companies are therefore looking for ways to produce their plans and forecasts in less time, with less effort and with better results, because in a volatile market environment characterized by crises, there can no longer be “business as usual”, even in corporate planning. This also increasingly applies to forecasts and simulations.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

Smarten

JUNE 20, 2023

Citizen Data Scientists Can Use Assisted Predictive Modeling to Create, Share and Collaborate! Gartner has predicted that, ‘40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

Predictive Modeling 52

Predictive Modeling Modeling Forecasting Data Science 52

Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. Another way of saying this is: given some desired optimal outcome Y, what conditions X should we put in place.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Smarten

MARCH 31, 2019

Predictive Analytics Techniques That Are Easy Enough for Business Users! There are a myriad of predictive analytics techniques and predictive modeling algorithms and you can’t expect your business users to understand and use them.

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Predictive Modeling Modeling Predictive Analytics Forecasting 40

DataRobot

JANUARY 20, 2022

The UK’s National Health Service (NHS) will be legally organized into Integrated Care Systems from April 1, 2022, and this convergence sets a mandate for an acceleration of data integration, intelligence creation, and forecasting across regions. Grasping the digital opportunity. Action to take.

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Data-driven Experimentation Modeling Predictive Modeling 145

Smarten

JANUARY 24, 2019

Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals. What is Automated Machine Learning?

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

Domino Data Lab

AUGUST 22, 2019

Data scientists and researchers require an extensive array of techniques, packages, and tools to accelerate core work flow tasks including prepping, processing, and analyzing data. Utilizing NLP helps researchers and data scientists complete core tasks faster. s lead may not be the optimal choice.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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. No advanced data science skills required.

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Predictive Analytics Analytics Predictive Modeling Forecasting 40

Smarten

MARCH 19, 2019

The Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics, published on October 31, 2018, includes the following strategic assumptions: By 2020, augmented analytics will be a dominant driver of new purchases of analytics and BI as well as data science and machine learning platforms, and of embedded analytics.

ROI 40

ROI Analytics Cost-Benefit Predictive Modeling 40

datapine

NOVEMBER 27, 2019

You simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on. Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis. 5) Collaborative Business Intelligence.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 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.

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