Sisense

FEBRUARY 25, 2021

One of the most important applications of data is using it to forecast the future. This is where forecasting analytics can be a game-changer in the decision-making process. In a recent webinar , I talked about how one of our customers, a performance theater owner, uses predictive analytics. Data-driven forecasting decisions.

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Smarten

MARCH 23, 2020

Predictive Analytics for Business Users = Assisted Predictive Modeling! These types of decision-making can be particularly dangerous to your business when they are applied to predicting and forecasting. Are you tired of using guesswork and opinions to make business decisions?

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Smarten

JULY 23, 2019

What is Predictive Analytics and How Can it Help My Business? What is predictive analytics? Put simply, predictive analytics is a method used to forecast and predict the future results and needs of an organization using historical data and a comprehensive set of data from across and outside the enterprise.

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Smarten

MARCH 13, 2018

That may seem like a tall order but with the right business intelligence software, you can provide predictive analytics for business users, including assisted predictive modeling that walks users through the analytical process and allows them to achieve the best results without a sophisticated knowledge of data analytical techniques.

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Smarten

AUGUST 5, 2022

Can Predictive Analytics Provide Accurate Results for My Business Without Burdening My Users? If your business is struggling to forecast and predict outcomes and results, your management team is probably considering predictive analytics. Understanding Assisted Predictive Modeling.

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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. Predictive analytics provides support for data-driven, fact-based decisions and enables insight, perspective and clarity for improved business agility and efficiency.

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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.

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CIO Business Intelligence

DECEMBER 11, 2023

For example, by tapping into real-time data with AI-enabled analytics, CFOs will be able to develop multiple scenarios for capital allocation, offering more forward-looking projections and more accurate forecasts. Artificial intelligence has already unlocked opportunities that most organizations never thought possible.

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Smarten

MARCH 7, 2024

Search Analytics is evolving at a rapid pace, and the concept of auto insights builds on the foundation of assisted predictive modeling and Clickless Analytics features, taking natural language processing (NLP) search analytics and predictive modeling to the next level.

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Smarten

JUNE 26, 2018

This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? Autoregressive Integrated Moving Average (ARIMA) predicts future values of a time series using a linear combination of its past values and a series of errors. p: to apply autoregressive model on series.

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Smarten

JUNE 29, 2018

This article looks at the ARIMAX Forecasting method of analysis and how it can be used for business analysis. What is ARIMAX Forecasting? This method is suitable for forecasting when data is stationary/non stationary, and multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity. About Smarten.

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IBM Big Data Hub

NOVEMBER 29, 2023

” No-code and low-code solutions for time series data exploration IBM introduced Downer to the realm where no-code and low-code solutions could build predictive models to provide faster insights. Downer was able to streamline modeling times with watsonx.ai In the realm of urban transportation, precision is pivotal.

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Smarten

MAY 17, 2019

These are just some of the examples of use cases that effectively illustrate how your business can benefit from predictive analytics in real-world scenarios. The benefits of advanced analytics and assisted predictive modeling are too numerous to provide a complete list here. Predictive Analytics Using External Data.

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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.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

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CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. The exam consists of 65 multiple-choice or multiple-response questions, which the candidate has 180 minutes to complete.

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Smarten

SEPTEMBER 28, 2022

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Plan and forecast accurately.’. Customer Churn.

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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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DataRobot

OCTOBER 19, 2021

By leveraging prediction and augmented decision-making, governments can address the needs of taxpayers proactively while quickly adapting to evolving circumstances. Many available forecasts provide less than four weeks notice at the state and county level. As these services have increased, so has the demand of constituent needs.

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Jedox

MAY 17, 2022

What Predictive Analytics Cannot Forecast. Predictive Analytics Example in Finance. A Brief History of Predictive Analytics. No industry has attempted to do more with predictive analytics than the financial services industry. What is Predictive Analytics? What Predictive Analytics Cannot Forecast.

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IBM Big Data Hub

APRIL 28, 2022

To truly understand the data fabric’s value, let’s look at a retail supply chain use case where a data scientist wants to predict product back orders so that they can maintain optimal inventory levels and prevent customer churn. That’s where the data fabric comes in. How does a data fabric impact the bottom line?

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CIO Business Intelligence

SEPTEMBER 5, 2023

It could allow analytics to become even more predictive by using data in AI algorithms to identify trends and patterns long before they become obvious. As a result, they’ve been able to generate 2,200 forecasts for 628 trucking lanes sampled from six U.S. In other words, it’s never about the new technology itself.

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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.

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IBM Big Data Hub

OCTOBER 5, 2022

Build planning models to improve supply chain management. You also build planning models to capture relationships and constraints so that you can change your driver assumptions and immediately see the impact on resources and capacity over time. The challenge faced by every company is matching supply with demand.

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CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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Smarten

JUNE 19, 2019

Encourage Data Literacy and Achieve Results with Assisted Predictive Modeling! If you want to include predictive analytics and forecasting in your planning process, there are numerous analytical techniques and algorithms at your disposal. In short, augmented analytics learning does not have to include years of study.

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Jedox

APRIL 16, 2020

What does your economic forecast look like for the foreseeable future? Most organizations lack the analytic maturity to be able to turn to their team of data scientists and have them build intelligent prescriptive models that easily light up the road to success. Forecast realistic outcomes. Turning Data into Insight.

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Smart Data Collective

APRIL 21, 2022

This will as well ensure accuracy in forecasting power generation rates and respective grid adjustments. Effective production forecast. Apart from the reactive response, the IoT for renewable energy includes effective production forecasts and improves grid stability. Many industries are helping drive growth for the IoT.

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Smarten

JUNE 8, 2022

Citizen Data Scientists can create new models, share models and collaborate, thereby improving business results and data literacy.’. Predicting Demand. According to technology research firm, Gartner, the number of Citizen Data Scientists will grow at five times the rate of traditional data scientists. Analyzing Customer Churn.

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DataRobot

SEPTEMBER 17, 2021

This information is powerful, but ultimately the grocer needs to decide how many mangos to order for that store, and the prediction doesn’t tell them exactly what to do. Stocking exactly the 2,700 mangos will lead to empty shelves and disappointed customers if the forecast underestimates demand. That is the ultimate decision.

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Smarten

JUNE 19, 2019

Encourage Data Literacy and Achieve Results with Assisted Predictive Modeling! If you want to include predictive analytics and forecasting in your planning process, there are numerous analytical techniques and algorithms at your disposal. In short, augmented analytics learning does not have to include years of study.

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Smarten

MAY 14, 2019

If a business wishes to optimize inventory, production and supply, it must have a comprehensive demand planning process; one that can forecast for customer segment growth, seasonality, planned product discounting or sales, bundling of products, etc. Predictive Analytics Using External Data. Learn More: Demand Planning.

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FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. The latest trends in business intelligence are reshaping the way organizations utilize data to gain a strategic advantage.

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IBM Big Data Hub

MAY 6, 2024

Enter the age of data-driven protocol assessment: using benchmarking tools and predictive modeling to gauge protocol intricacies and forecast eligible patient numbers, which then inform protocol adjustments. It’s crucial to evaluate the feasibility of trials and refine protocols using evidence-based strategies.

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DataRobot

NOVEMBER 24, 2021

But it had trouble predicting sellout volume at scale and automating the necessary modeling and forecasting. To meet these needs, it turned to AI, running the DataRobot AI Cloud on AWS instead of following its previously backbreaking, manual model-building process. By the year 2030, AI will deliver economic growth of $15.7

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DataRobot

JUNE 4, 2021

As new algorithms prove their merit, they are incorporated into DataRobot’s algorithm repository, and the platform continues to adapt and evolve even after models are deployed through a concept called continuous learning. Forecasting In-Store Foot Traffic. Here, we have a model that predicts foot traffic for a chain of coffee shops.

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Smarten

NOVEMBER 14, 2017

Predictive Analytics for the Faint of Heart! Assisted Predictive Modeling , Predictive Analytics. They don’t want to have to try to unravel the complicated world of data analytics and be forced to choose forecasting techniques or predictive models. Plug n’ Play Predictive Analysis.

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Smarten

APRIL 17, 2018

How Can Assistive Predictive Modeling Help My Business Users? If you are wondering how and why predictive analytics software has expanded into the self-serve business user market, the reason is simple. Predictive Analytics Software should be easy to implement, easy to personalize and easy to use.

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