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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IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Smarten

SEPTEMBER 14, 2018

Just Simple, Assisted Predictive Modeling for Every Business User! You can’t get a business loan, join with a business partner, successfully bid on a project, open a new location, hire the right employees or plan for the future without predictive analytics. No Guesswork!

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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”).

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Smarten

APRIL 10, 2023

Investment in predictive analytics benefits everyone in the organization, including business users and team members, data scientists and the organization in general. Team members can bridge the gap of data science skills so they don’t have to wait for IT or data scientists to help them produce a report or perform analytics.

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CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. How to prepare: No prior computer science or programming knowledge is necessary.

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DataRobot Blog

JULY 28, 2022

This article presents a case study of how DataRobot was able to achieve high accuracy and low cost by actually using techniques learned through Data Science Competitions in the process of solving a DataRobot customer’s problem. Sensor Data Analysis Examples. The Best Way to Achieve Both Accuracy and Cost Control.

Data Science 72

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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.’ Forecasting. Access to Flexible, Intuitive Predictive Modeling. Trends and Patterns. Classification.

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IBM Big Data Hub

NOVEMBER 29, 2023

But Downer envisioned a partnership that would allow them to delve deeper into the data, unearthing more insights that could add value to operations. They combined forces with the experts at IBM to reach toward the expanding horizons of data science. Downer was able to streamline modeling times with watsonx.ai

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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. Broken models are definitely disruptive to analytics applications and business operations.

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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.

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CIO Business Intelligence

JUNE 7, 2022

Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance. Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes.

Data Analytics 133

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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.

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Smarten

JANUARY 24, 2019

Business users can leverage machine learning and assisted predictive modeling to achieve the best fit and ensure that they use the most appropriate algorithm for the data they wish to analyze. Not so long ago, this type of Advanced Analytics would have demanded the services of a full-time, trained data scientist.

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Smarten

MARCH 18, 2019

Data Science and Predictive Analytics Made Simple! Imagine a world where data science and predictive analytics tools are created for business users! Contact Us if you want an Advanced Analytics Solution that will support business users and enhance business results.

Predictive Analytics 40

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Smarten

SEPTEMBER 11, 2017

Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Take plug n’ play predictive analytics for example.

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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.

Business Intelligence 361

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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.

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Smarten

DECEMBER 3, 2023

‘Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms. We should probably explain before we move on.

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Key Performance Indicator Analytics IT Predictive Analytics 52

Sisense

SEPTEMBER 9, 2019

If you lack a data science team, integrating BigSquid with your open-platform BI tool is a powerful way to achieve the horsepower of data science while maintaining the ease of use that the average business user requires. Then we ran Kraken’s machine learning and predictive modeling engine to get the results.

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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

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.

Predictive Analytics 40

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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

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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

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

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

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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

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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.

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Data Science and Beyond

JANUARY 8, 2017

However, it’s important to remember that all models are wrong (but some models are useful) , and that the lifetime value of active customers is unknowable since it involves forecasting of uncertain quantities. I’ve successfully used the package on a real dataset and have contributed some small fixes and improvements.

Statistics 100

Statistics Modeling Predictive Modeling Marketing 100

DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning.

Forecasting 81

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Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. This may give a more accurate representation in the variability of predictions.

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Cloudera

APRIL 11, 2023

As the entire Cloudera Data Platform is built on open source projects, we find it crucial to participate in and contribute back to the community. Applied ML Prototypes (AMPs) are fully built end-to-end data science solutions that allow data scientists to go from an idea to a fully working machine learning model in a fraction of the time.

Forecasting 72

Forecasting Machine Learning Recreation/Entertainment Sales 72

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 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

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. Natural Language Processing.] together at Stanford University.

Deep Learning 111

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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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