Smarten

JUNE 8, 2022

‘Citizen Data Scientists can create new models, share models and collaborate, thereby improving business results and data literacy.’. In this article, we provide some examples of what a Citizen Data Scientist can do to advance the goals and interests of the organization and optimize their productivity and performance.

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IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. Maintenance schedules can use AI-powered predictive analytics to create greater efficiencies.

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IBM Big Data Hub

MAY 6, 2024

Predicting site performance, spotting underperforming sites and formulating timely interventions are essential. Optimize protocols using historical and synthetic data Complex and stringent protocols are notorious for delaying clinical trials and eroding patient engagement.

Advertising 57

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FineReport

APRIL 9, 2024

Optimized Operational Efficiency: These tools streamline processes and resource allocation, leading to cost savings and improved resource utilization. The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance.

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Smart Data Collective

SEPTEMBER 30, 2021

Drought Risk Assessment and Prediction. 2 Through artificial intelligence-based prediction, there can be improvement in decision making regarding droughts and better methods and timing employed to ensure optimal water resource allocation and disseminating information ahead of drought events. Wildlife Conservation.

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Smarten

MAY 17, 2019

If you can easily integrate data from sources outside the business, you can provide a more comprehensive picture for predicting and forecasting results and anticipating the needs of the market. Marketing Optimization. Customer Targeting. Product and Service Cross-Sell and Upsell. Customer Churn. Fraud Mitigation. Loan Approval.

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Smarten

MAY 13, 2019

The cost of acquiring a new customer includes marketing and advertising, resources and personnel, customer support, search engine optimization and more. Use Predictive Analytics to identify at risk customers and issues that will impact customer churn and customer retention. Marketing Optimization. Loan Approval.

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Smarten

JANUARY 31, 2019

Put simply, business Intelligence uses historical data to reveal where the business has been, and managers can use this data to predict competitive response and discover what is changing in customer buying behavior and in sales. How is Advanced Analytics Different from Business Intelligence?

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Smarten

AUGUST 21, 2019

Assisted Predictive Modeling – These tools enable the average business user to leverage sophisticated predictive algorithms without requiring statistical or data science skills. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

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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 also helps businesses forecast and decrease customer churn (the rate at which a company loses customers), a widespread use of big data. Many stock market transactions use ML. Computer vision fuels self-driving cars.

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Smarten

APRIL 2, 2019

Business markets and competition are moving much more quickly these days and predicting, planning and forecasting is more important than ever. Advanced analytics is the logical tool to help a business optimize its investments and achieve its goals.

Analytics 40

Analytics Predictive Modeling Visualization Cost-Benefit 40

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.

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Smarten

NOVEMBER 19, 2018

Today’s self-serve predictive analytics and forecasting tools are designed to support business users and data analysts alike. What is Predictive Analytics? Predictive analytics is the process of forecasting or predicting business results for planning purposes.

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Business Objectives Predictive Analytics Analytics Forecasting 40

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.

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Smarten

MAY 15, 2019

The enterprise does not want to risk its reputation with unanticipated downtime or the loss of revenue for its customers. Your business can leverage Predictive Analytics to plan for and anticipate maintenance, investment, changes in resources and training requirements and supply chain management for parts, shipping, etc.

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Predictive Analytics Management Analytics Cost-Benefit 10

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

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BI-Survey

MARCH 16, 2021

Corporate planning and forecasting needs to be carried out efficiently, in shorter cycles and must be updated quickly for well-founded decision-making. Increasing dynamics demand adjustments to the corporate management process – as well as strategic planning and forecasting – to meet growing requirements.

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IBM Big Data Hub

DECEMBER 20, 2023

Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available.

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BI-Survey

MARCH 16, 2021

Corporate planning and forecasting needs to be carried out efficiently, in shorter cycles and must be updated quickly for well-founded decision-making. Increasing dynamics demand adjustments to the corporate management process – as well as strategic planning and forecasting – to meet growing requirements.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

IBM Big Data Hub

JULY 5, 2023

With a good digital twin, it’s possible to predict how an asset will perform under certain conditions and what it’s projected lifespan will be. Read this blog post to explore how digital twins can help you optimize your asset performance. A sound ALM strategy ensures compliance no matter where data is being stored.

Strategy 59

Strategy Management IoT Cost-Benefit 59

FineReport

APRIL 24, 2024

By presenting comprehensive insights through visualizations, decision-makers can assess trends, risks, and opportunities with greater clarity. This foresight empowers organizations to proactively prepare for upcoming shifts or developments based on credible analytical forecasts.

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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. Another way of saying this is: given some desired optimal outcome Y, what conditions X should we put in place.

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DataRobot Blog

JUNE 24, 2022

Thanks to the increasingly rapid evolution of AI and advances in machine learning, the real estate industry has a more vivid picture of future risk and opportunities across all different market segments: offices, residential, retail, logistics, hotels, OPRE and data centers.

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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. Public sector data sharing. Grasping the digital opportunity.

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Smarten

MARCH 19, 2019

In today’s competitive business market, every senior executive looks at risk, value and calculations like return on investment (ROI) and total cost of ownership (TCO) before approving a budget. As business organizations fight for competitive advantage, funding for projects and large expenditures can fall by the wayside.

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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. Industries harness predictive analytics in different ways.

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datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

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Jet Global

SEPTEMBER 1, 2023

But we’re also seeing its use expand in other industries, like Financial Services applications for credit risk assessment or Human Resources applications to identify employee trends. Using the information from predictive analytics can help companies—and business applications—suggest actions that can affect positive operational changes.

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Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. In an ETL process, data transformations can be optimized before loading, which may improve performance for data-intensive transformations.

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Jet Global

MAY 1, 2023

Healthcare is forecasted for significant growth in the near future. CFO Priorities Manage expenses and cash flow Enable profitable growth Contain risk Plan for the future Connect the Dots Do the math. Your analysis should also take into consideration the opportunity cost and project risk. Present your business case.

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