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 machine learning? This post will dive deeper into the nuances of each field.

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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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CIO Business Intelligence

NOVEMBER 14, 2022

Decision intelligence seeks to update and reinvent decision support systems with a sophisticated mix of tools including artificial intelligence (AI) and machine learning (ML) to help automate decision-making. Analytics, Data Science XLSTAT is an Excel data analysis add-on geared for corporate users and researchers.

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CIO Business Intelligence

FEBRUARY 16, 2023

The next goal, with the aid of partner Findability Sciences, will be to build out ML and AI pipelines into an information delivery layer that can support predictive and prescriptive analytics. “As We have a learning curve at our end to build the right skill set within us.” The company’s Findability.ai

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IBM Big Data Hub

JULY 27, 2022

Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following: Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT infrastructure components, applications and performance-monitoring tools. Predictive analytics to show what will happen next.

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Sisense

JUNE 30, 2020

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. Predictive analytics is the most beneficial, but arguably the most complex type.

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Domino Data Lab

JUNE 2, 2019

Secondly, I talked backstage with Michelle, who got into the field by working on machine learning projects, though recently she led data infrastructure supporting data science teams. Just doing machine learning is not enough, and sometimes not even necessary.”. First off, her slides are fantastic! Nick Elprin.

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Jedox

JULY 31, 2018

Part one of our blog series explored how people are the driving force behind the digital transformation and how it is fueled by artificial intelligence and machine learning. Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive.

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BizAcuity

MARCH 31, 2022

Predictive Analytics: Predictive analytics is the most talked about topic of the decade in the field of data science. The aim of predictive analytics is, as the name suggests, to predict and forecast outcomes. Prescriptive Analytics: Prescriptive analytics is the most complex form of analytics.

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Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Identify those most at risk or most affected by a problem more accurately by using predictive analytics.

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AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

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FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

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Alation

MARCH 21, 2023

How is data analytics used in the travel industry? The travel and tourism industry can use predictive, descriptive, and prescriptive analytics to make data-driven decisions that ultimately enhance revenue, mitigate risk, and increase efficiencies.

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FineReport

APRIL 26, 2023

.” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting.

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DataRobot Blog

NOVEMBER 12, 2019

by Jen Underwood. Why didn’t I think of that? Sometimes we get caught up in our day-to-day lives and don’t stop to see if we are solving the right, bigger picture problems. Read More.

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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. 4) Predictive And Prescriptive Analytics Tools.

Business Intelligence 361

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datapine

DECEMBER 4, 2019

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? 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. Prescriptive Analytics: What should we do?

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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. How do predictive and prescriptive analytics fit into this statistical framework?

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Smarten

SEPTEMBER 9, 2024

‘To fulfill the role of a Citizen Data Scientist, business users today can leverage augmented analytics solutions; that is analytics that provide simple recommendations and suggestions to help users easily choose visualization and predictive analytics techniques from within the analytical tool without the need for expert analytical skills.’

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Andrew White

JANUARY 11, 2021

The data suggests several things: The work of traditional analytics and BI continues towards democratization in the business unit directly, we call this domain analytics in our research, part of domain D&A. Yes, prescriptive and predictive analytics remain very popular with clients.

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Smarten

APRIL 11, 2018

Gartner defines a Citizen Data Scientist as ‘a person who creates or generates models that leverage predictive or prescriptive analytics but whose primary job function is outside of the field of statistics and analytics.’ What is a Citizen Data Scientist (Citizen Analyst)?

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Smarten

SEPTEMBER 9, 2024

Gartner defines a citizen data scientist as, ‘ a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’ So, let’s get started. What is a Cititzen Data Scientist? Who is a Citizen Data Scientist?

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Jet Global

MAY 1, 2023

Diagnostic Analytics: No longer just describing. Predictive Analytics: If x, then y (e.g., Prescriptive Analytics: Here’s what to do to achieve a desired outcome (e.g., In the same way, embedded analytics lean towards descriptive and diagnostic. Interest in predictive analytics continues to grow.

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