BizAcuity

FEBRUARY 21, 2025

Without the right expertise, companies risk misconfigurations or suboptimal integrations that dont deliver the desired results. This enables businesses to anticipate potential disruptionswhether in supply chains, sales cycles, or customer demandbefore they occur, allowing for better preparedness and risk mitigation.

Dashboards 52

Dashboards Optimization Finance Sales 52

Cloudera

AUGUST 25, 2020

One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. . This is critically important for predicting risk exposures. Prescriptive analytics provides decision-makers with thousands of potential future scenarios.

Prescriptive Analytics 74

Prescriptive Analytics Technology Machine Learning Risk 74

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.’ Competitive Changes. Market Changes. Trends and Patterns.

Predictive Analytics 69

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 69

IBM Big Data Hub

JANUARY 25, 2024

Considering that IDC surveyed 37% of companies that manage spare parts inventory by using spreadsheets, email, shared folders or an uncertain approach, it becomes evident that this practice carries more risk than it might seem. 2 Unless your demand forecasting is accurate, adopting a reactive approach might prove less efficient.

Optimization 73

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 73

Sisense

JUNE 30, 2020

Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. And the data is as granular as the patient lists at individual family doctors’ surgeries.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Will this next trade return a profit?

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

AWS Big Data

MARCH 26, 2024

You can use third-party data products from AWS Marketplace delivered through AWS Data Exchange to gain insights on income, consumption patterns, credit risk scores, and many more dimensions to further refine the customer experience. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

Cloudera

MARCH 2, 2018

Applying data analytics and machine learning to large raw datasets will likely also yield us new and unexpected insights as these techniques and tools allow us to unearth patterns and seek potential explanations for those in contrast to responding to a predefined set of questions.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43

BizAcuity

MARCH 31, 2022

85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Cloudera

JULY 18, 2018

The combined solution is the right starting point for introducing machine learning and AI into clinical workflow and care delivery, enabling enterprises to take advantage of complete descriptive, predictive, and prescriptive analytic capabilities.

Machine Learning 51

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 51

Domino Data Lab

JUNE 2, 2019

Trying to dissect a model to divine an interpretation of its results is a good way to throw away much of the crucial information – especially about non-automated inputs and decisions going into our workflows – that will be required to mitigate existential risk. Because of compliance. Admittedly less Descartes, more Wednesday Addams.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

DataRobot Blog

MARCH 15, 2022

Integrating and aligning data across organizations (acute, primary, mental health, social care, and third sector) can be challenging, but is essential to enable forward-looking population health management, strengthen risk stratification, and support the redesign of care pathways.

Prescriptive Analytics 52

Prescriptive Analytics Digital Transformation Data-driven Machine Learning 52

IBM Big Data Hub

JANUARY 17, 2023

With this capability, not only can data-driven companies operationalize data science models on any cloud while instilling trust in AI outcomes, but they are also in a position to improve the ability to manage and govern the AI lifecycle to optimize business decisions with prescriptive analytics. Start a trial. AI governance.

Data-driven 56

Data-driven Enterprise Data Governance Data Science 56

Alation

MARCH 21, 2023

What’s more, many companies struggle with rigid legacy technologies that increase the risk of a data breach. Otherwise, they risk a data privacy violation. How is data analytics used in the travel industry? Regulatory compliance Additionally, this PII is often highly regulated.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Jedox

JANUARY 29, 2019

Fifty percent of global fp&a teams are looking to implement predictive analytics by 2020*, and seventy-two percent rate “Predictive Forecasting and Planning” as either “very important or “important” for their company**. Predictive Analytics for Sales Forecasting. Making AI Real (Part 2).

Predictive Analytics 41

Predictive Analytics Forecasting Sales Analytics 41

IBM Big Data Hub

JULY 6, 2023

Some examples of data science use cases include: An international bank uses ML-powered credit risk models to deliver faster loans over a mobile app. An AI-based medical assessment platform analyzes medical records to determine a patient’s risk of stroke and predict treatment plan success rates.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

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.

Statistics 52

Statistics Data mining Visualization Reporting 52

FineReport

APRIL 26, 2023

Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting. Prescriptive Analytics provides precise recommendations to respond to the query, “What should I do if ‘x’ occurs?”

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. 4) Predictive And Prescriptive Analytics Tools. Data Automation.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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?

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Statistics 157

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? Mobile analytics.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Smarten

JULY 30, 2024

‘Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background.’ A misstep in any of these areas can create risk, damage your business reputation, or put you years behind your competition.

Predictive Analytics 64

Predictive Analytics Prescriptive Analytics Predictive Modeling Analytics 64

Andrew White

JANUARY 11, 2021

Some data is more a risk than valuable. What are you seeing as the differences between a Chief Analytics Officer and the Chief Data Officer? Risk Management (most likely within context of governance). Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

OCTOBER 9, 2024

According to a recent Forbes article, “the prescriptive analytics software market is estimated to grow from approximately $415M in 2014 to $1.1B This continuous flow of data can shift decision-making from reactive to proactive, empowering businesses to adapt quickly and minimize risks.

Prescriptive Analytics 52

Prescriptive Analytics IoT Internet of Things Cost-Benefit 52

Alation

AUGUST 26, 2021

Privacy, Risk and Compliance. Augmented Analytics. DI empowers analysts to apply augmented analytics to applications, supporting predictive and prescriptive analytics use cases. Data intelligence has thus evolved to answer these questions, and today supports a range of use cases. Cloud Transformation.

Metadata 64

Metadata Data Governance Dashboards Software 64

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?

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52

CIO Business Intelligence

FEBRUARY 13, 2025

Artificial intelligence (AI)-enabled systems are driving a new era of business transformation, revolutionizing industries through prescriptive analytics, personalized customer experiences and process automation. Generative AI risks. Promoting fairness and inclusivity in AI systems builds trust and mitigates reputational risks.

Risk 116

Risk Data-driven Finance Risk Management 116

Jet Global

MAY 1, 2023

Positioning Embedded Analytics for Each Executive Here are some tips on understanding executives’ priorities and getting them on board with the project. Show how embedded analytics will enhance sales and marketing through better demos and shorter sales cycles. It will help to eliminate some of the development risks.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

CIO Business Intelligence

DECEMBER 19, 2024

As organizations struggle with the increasing volume, velocity, and complexity of data, having a comprehensive analytics and BI platform offers real solutions that address key challenges, such as data management and governance, predictive and prescriptive analytics, and democratization of insights.

Sales 122

Sales Analytics Key Performance Indicator Prescriptive Analytics 122