#prescriptiveanalytics

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Predictive vs Prescriptive vs Descriptive Analytics Explained 

Business analytics leveraging data patterns for strategic moves comes in three key approaches – descriptive identifying “what has occurred", predictive forecasting “what could occur” and prescriptive recommending “what should occur” to optimize decisions. We decode the science behind each for aspiring analytics professionals.

Descriptive analytics convert volumes of historical data into insightful summaries around metrics revealing business health, customer trends, operational efficiencies etc. using direct analysis, aggregation and mining techniques producing current reports. 

Predictive analytics forecast unknown future probabilities applying statistical, econometric and machine learning models over existing data to minimize uncertainties and capture emerging behaviors early for mitigation actions. Risk models simulate scenarios balancing upside/downside tradeoffs. 

Prescriptive analytics take guidance one step further by dynamically recommending best decision options factoring in key performance indicators for business objective improvements after predicting multiple futures using bell curve simulations. Optimization algorithms deliver preferred actions.

While foundational data comprehension and wrangling abilities fuel all models – pursuing analytics specializations focused on statistical, computational or operational excellence boosts career-readiness filling different priorities global employers seek!

Posted By:

Aditi Borade, 4th year Barch,

Ls Raheja School of architecture 

Disclaimer: The perspectives shared in this blog are not intended to be prescriptive. They should act merely as viewpoints to aid overseas aspirants with helpful guidance. Readers are encouraged to conduct their own research before availing the services of a consultant.

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[yashmedica]

Big Data Revolution in Healthcare: Unveiling Insights with AI, Machine Learning & Top Players like McKesson, Cognizant & Epic Systems

The potential of service type insights in the big data healthcare market. Explore descriptive, predictive, and prescriptive analytics, key trends, and innovations from leading companies. Invest wisely with insights into market share, growth trajectories,

Big Data in Healthcare Market: The Potential of Service Type Insights (Descriptive, Predictive, Prescriptive) The big data revolution is transforming the healthcare landscape, with vast amounts of patient data holding the key to improved clinical decision-making, personalized medicine, and optimized healthcare operations. But how is this data being utilized? Enter service type insights – an…

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Unlocking Success: Principles for Effective Supply Chain Network Design

Originally Published on: SpendEdge |Unlocking Success: Principles to Guide Effective Supply Chain Network Design 

In the ever-evolving landscape of global trade, where goods traverse continents and supply routes span the globe, lies the heartbeat of every thriving enterprise: the supply chain. Yet, within this intricate web of logistics, inventory management, and strategic decision-making, lies both the promise of prosperity and the peril of inefficiency.

#SupplyChainOptimization #OperationalExcellence

Unveiling the Importance of Supply Chain Network Design

Visualize a seamless flow of goods, meticulously orchestrated to minimize costs, maximize efficiency, and deliver products to eager consumers precisely when and where they’re needed. This is the vision propelling supply chain network optimization – the pursuit of optimal efficiency amid a sea of complexity.

But why does it matter? In today’s fast-paced, hyper-connected world, where market dynamics shift at the blink of an eye, a well-coordinated supply chain isn’t just a competitive advantage – it’s a survival imperative. From reducing costs and enhancing visibility to mitigating risks and seizing opportunities, the stakes have never been higher.

#GlobalCommerce #OperationalEfficiency

Navigating the Labyrinth: Understanding Supply Chain Network Design

Understanding the significance of supply chain network design is paramount in modern business landscapes. Research suggests that a significant portion of supply chain expenses are established during the initial design phase. Neglecting this crucial aspect can lead to significant financial repercussions and hinder long-term success.

When examining the intricacies of a global supply chain network – its pathways, timelines, associated costs, and revenue streams – numerous critical inquiries emerge. Questions such as: Why are our sole suppliers located overseas? What drives the proliferation of warehouses, and why are they situated in specific locations? Why does excess inventory persist, and what prompts the continuous influx of orders? Why do freight and transportation expenses remain exorbitant? Assessing the efficiency of the current network design becomes imperative.

Moreover, scrutinizing whether the supply chain aligns with sustainability objectives is vital. Is the design conducive to minimizing environmental impact and optimizing resource utilization? Addressing these inquiries is pivotal for enhancing operational efficiency and achieving long-term sustainability goals.

#SupplyChainEfficiency #SustainabilityGoals

Factors to Consider While Designing a Supply Chain Network Model

When embarking on the design of a supply chain network model, several crucial factors must be considered to ensure its effectiveness and alignment with organizational objectives. Here’s a breakdown of key considerations:

Define Objectives: Clearly articulate the objectives of the supply chain design, ensuring alignment with broader enterprise goals. Consider factors such as capacity constraints, inventory management strategies, lead times for replenishment, customer service level requirements, and the strategic positioning of facilities and sources.

Data Collection: Gather comprehensive data including historical performance metrics, forecasts, market trends, and customer demand patterns. This data serves as the foundation for informed decision-making throughout the design process.

Utilize Optimization Tools: Employ advanced network optimization tools and software to develop a dynamic model of the supply chain. These tools allow for the incorporation of various parameters, constraints, and scenarios to create a robust and adaptable framework.

Build a “Living” Model: Develop a flexible and iterative model that can evolve with changing business dynamics. Incorporate real-time data feeds and feedback mechanisms to ensure the model remains responsive to market shifts and internal changes.

Validation through Scenarios: Validate the effectiveness of the model by running simulated “what-if” scenarios based on historical data and known outcomes. This validation process helps identify potential bottlenecks, vulnerabilities, and areas for improvement within the proposed network design.

Finalize and Implement: Once the model has been thoroughly validated and refined, finalize the supply chain network design and proceed with its implementation. Collaborate closely with stakeholders across departments to ensure smooth integration and alignment with existing operational processes.

By systematically addressing these factors, enterprises can develop a robust and optimized supply chain network model that effectively supports their strategic objectives and adapts to evolving market dynamics.

#SupplyChainModeling #OperationalFlexibility

The Power of a Digital Twin: Revolutionizing Supply Chain Management

A Digital Twin represents a virtual replica of an entire value chain, leveraging real-time or near-real-time data from multiple sources to mirror all essential relationships and functions. By utilizing a Digital Twin, organizations gain the ability to explore a multitude of variables affecting supply chain network design within a secure and controlled environment, prior to making actual operational decisions.

Moreover, when coupled with a Prescriptive Analytics Platform, a Digital Twin transcends predictive capabilities, offering insights into optimal courses of action. It empowers leaders to navigate through various factors, filter out impractical scenarios, assess trade-offs, quantify associated risks, and identify the most suitable path to achieve predefined objectives.

In essence, the integration of a Digital Twin into supply chain management facilitates more successful network design endeavors, resulting in enhanced financial and operational performance. This holds particularly true when transitioning from conventional tools traditionally used in such contexts.

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Who’s on a quest to develop advanced data science capabilities? One of my analytics team’s strategic expansion brought together diverse talents in statistics, applied math, and engineering.

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Breaking down Business Analytics vs Business Intelligence Master's

With data empowering strategic decisions across every function, demand for specialized business analytics and business intelligence graduate degrees is seeing unprecedented growth from ambitious professionals worldwide. 

But what’s the difference between these two seemingly overlapping study areas when it comes to curriculum focus, skills developed and career outcomes for master's students? Let’s explore key insights.

While both degrees equip students to harness statistical models, derive quantifiable insights and visualize data patterns influencing plans – master’s in business intelligence develop core IT and organizational decision-making abilities whereas master’s in business analytics emphasize advanced statistical and computational competencies relevant for private sector roles.

Business intelligence master's teach technologies like data warehousing, OLAP cubes modeling and data mining for effective management information systems leveraging enterprise-wide internal data flows. Graduates can strategize planning initiatives or streamline processes as analyst or managerial roles. 

Business analytics master's offer more rigorous statistical discipline exploring predictive, prescriptive and diagnostic high-level analytics aided by programming languages like Python and R while also covering some database query tools. Those opting for research or data scientist, quantitative strategist or analytics architect trajectories find these curriculums enable sharper technical readiness for careers leveraging external and unstructured big data analytics. 

Depending on whether you desire developing IT systems insights or statistical modeling competencies - choosing the right data-driven business master’s opens up immense opportunities to power data-informed leadership in international job markets today!

#businessanalytics  #businessintelligence  #master's

#dataempowering

#envoyoverseas  #ethicalcounselling #envoyeducation

#developcoreITabilities #advancedstatisticalcompetencies

#streamlineprocess #OLAPcubes modeling

#predictivanalytics  #prescriptiveanalytics  #disgnosticanalytics

#careeroutcomes

#pythonandR

#datainformedleadership

-Hithika Mekala

Disclaimer: The perspectives shared in this blog are not intended to be prescriptive. They should act merely as viewpoints to aid overseas aspirants with helpful guidance. Readers are encouraged to conduct their own research before availing the services of a consultant.

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Unveiling the Power of Prescriptive Analytics: Shaping the Future of Decision-Making 📊

Hey everyone! Today, let's delve into the exciting realm of prescriptive analytics and explore how this cutting-edge technology is revolutionizing data-driven decision-making across industries. 🌟

Prescriptive analytics is an advanced form of data analysis that goes beyond descriptive and predictive analytics to provide actionable insights and recommendations. By leveraging mathematical algorithms, machine learning models, and optimization techniques, prescriptive analytics helps organizations optimize outcomes, make informed decisions, and maximize efficiency. Whether it's optimizing supply chain operations, enhancing marketing strategies, or improving healthcare outcomes, prescriptive analytics empowers businesses and professionals to proactively address complex challenges and capitalize on opportunities. 📈

Here are some key aspects and benefits of prescriptive analytics:

Optimization: Prescriptive analytics models identify the best course of action to achieve specific goals and objectives, optimizing resource allocation and operational efficiency.

Decision Support: By simulating different scenarios and outcomes, prescriptive analytics assists decision-makers in evaluating trade-offs and making informed choices.

Real-Time Insights: Prescriptive analytics enables real-time decision-making by continuously analyzing data streams and adapting strategies based on changing conditions.

Risk Management: Prescriptive models assess risk factors and recommend proactive measures to mitigate risks and uncertainties in various domains.

Personalized Recommendations: In consumer-facing applications, prescriptive analytics delivers personalized recommendations and experiences tailored to individual preferences.

Let's celebrate the transformative potential of prescriptive analytics in driving innovation and unlocking new possibilities! Are you intrigued by prescriptive analytics or have you witnessed its impact in your industry? Share your thoughts and experiences below! 📊💬

Using hashtags to connect with analytics enthusiasts: #PrescriptiveAnalytics #DataDriven #DecisionMaking #MachineLearning #Optimization #BusinessIntelligence #AI #BigData #TechInnovation #DigitalTransformation 🌐

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Career Transition from Manufacturing to Data Science | Skillslash Tips and Tricks | Skillslash

Skillslash would be an educational technology firm founded by IIT KGP alumni only with the mission of assisting students and working adults in successful career advancement. We recognise the critical need for high-quality programmes in ever-evolving technologies. Therefore, they provide ground-breaking classes in fields such as analytics, data science, artificial intelligence, supervised learning, and computer vision, amongst many others.

Our courses are meant to assist hopefuls such as working professionals and grads, as we understand the fundamental and important requirements. Our instructors are highly skilled and experienced experts who will teach, explain, and assist you in learning the material. We offer subject matter expertise to our students by collaborating with premier entrepreneurs in India.

With specialised technical training offered at their institute, students may be sure to receive high-quality teaching. We work hard to spread awareness about the importance of academic credentials. Skillslash is really the ideal e-learning area for experts, with a well-designed course and also an acute focus on important learning.

Learn more about data analytics and its many forms of statistics by watching this short video.

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Still confused before making decisions? It is time to get a customized #PredictiveAnalysis software for your business model and take a confident step ahead. How it will help your business, now by taking a read from https://bit.ly/2WmlFJN

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Hello to everyone from the 30th floor. 🏙💻🌹 Selam arkadaşlar yeni bir grup kurduk beni takip eden arkadaşlarla birbirimizi tanıma önerilerde bulunma şeklinde sohbetler ediyoruz ve buluşmalar gerçekleştireceğiz ilerleyen zamanlarda kariyer sohbetleri yapacağız iyiki varsınız sizleri bu gönderimin altında bekliyorum bakalım kimler bizimle 💗🤗 . . #AI #Analytics #BI #BigData #Database #DataEngineering #DataLake #DataScience #DataWarehouse #DeepLearning #GraphDB #IIoT #IoT #LinkedData #MachineLearning #NoSQL #OpenData #codergallery #PredictiveAnalytics #PrescriptiveAnalytics #SmallData #SmartData #Statistics (Türkiye Iş Bankası Genel Müdürlüğü) https://www.instagram.com/p/BuJUNNwgU3b/?utm_source=ig_tumblr_share&igshid=19itltf298nlu

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AI and Machine Learning: The Powerhouse Behind Advanced Life Science Analytics

The tide is turning in life sciences! Explore how descriptive, predictive, and prescriptive analytics are transforming the industry. Discover the applications, emerging trends in AI and machine learning, and top innovators shaping the future of healthcare

How Descriptive, Predictive, and Prescriptive Analytics are Transforming Life Sciences The life sciences industry is experiencing a data revolution. With the increasing amount of healthcare data, advanced analytics are essential for driving innovation and efficiency. However, understanding the strengths and uses of different types of analytics is important. Let’s explore the most common…

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Global Predictive and Prescriptive Analytics Market Size, Status and Forecast 2021-2027

Big data explosion has rapidly become a pivotal tool for the business intelligence sector. This powerful data stream is building the momentum and magnitude for the predictive and prescriptive analytics market. This platform helps swiftness of diverse data, combining with big data, and utilizing better models and business outcomes of leading healthcare organizations. It improves quick-decision, profits, measures social media influence and tries to avert scams and frauds, through the application of advanced analytics and decision optimization.

In 2021, the global Predictive and Prescriptive Analytics market size will be US$ 8159.1 million and it is expected to reach US$ 16810 million by the end of 2027, with a CAGR of 12.8% during 2021-2027.

Download FREE Sample of this Report @ https://www.grandresearchstore.com/report-sample/global-predictive-prescriptive-analytics-2021-2027-296

This report focuses on the global Predictive and Prescriptive Analytics status, future forecast, growth opportunity, key market, and key players. The study objectives are to present the Predictive and Prescriptive Analytics development in North America, Europe, Japan, China, Southeast Asia, India, etc.

Global Predictive and Prescriptive Analytics Scope and Market Size

Predictive and Prescriptive Analytics market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Predictive and Prescriptive Analytics market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2016-2027.

Segment by Type

Software

Service

Segment by Application

Defense and aerospace sector

Intelligence organization

Agriculture

Retail sector

Educational organizations

Healthcare

Transportation and logistics

By Region

North America

Europe

Japan

China

Southeast Asia

India

By Company

Salesforce

SAS Institute

IBM

SAP AG

Oracle

Angoss Software

Teradata

Microsoft

Accenture

Get the Complete Report & TOC @ https://www.grandresearchstore.com/ict-and-media/global-predictive-prescriptive-analytics-2021-2027-296

Table of content

1 Report Overview 1.1 Study Scope 1.2 Market Analysis by Type 1.2.1 Global Predictive and Prescriptive Analytics Market Size Growth Rate by Type (2021-2027) 1.2.2 Software 1.2.3 Service 1.3 Market by Application 1.3.1 Global Predictive and Prescriptive Analytics Market Share by Application (2021-2027) 1.3.2 Defense and aerospace sector 1.3.3 Intelligence organization 1.3.4 Agriculture 1.3.5 Retail sector 1.3.6 Educational organizations 1.3.7 Healthcare 1.3.8 Transportation and logistics 1.4 Study Objectives 1.5 Years Considered 2 Executive Summary 2.1 Global Predictive and Prescriptive Analytics Market Size 2.2 Predictive and Prescriptive Analytics Market Size by Regions 2.2.1 Predictive and Prescriptive Analytics Growth Rate by Regions (2021-2027) 2.2.2 Predictive and Prescriptive Analytics Market Share by Regions (2021-2027) 2.3 Industry Trends 2.3.1 Market Top Trends 2.3.2 Market Use Cases 3 Key Players 3.1 Predictive and Prescriptive Analytics Revenue by Players (2020-2021) 3.2 Predictive and Prescriptive Analytics Key Players Headquaters and Area Served 3.3 Key Players Predictive and Prescriptive Analytics Product/Solution/Service 3.4 Date of Enter into Predictive and Prescriptive Analytics Market 3.5 Mergers & Acquisitions, Expansion Plans 4 Breakdown by Type and

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Our world is encouraging Prescriptive Analytics like never before! #prescriptiveanalytics https://www.instagram.com/p/Bow0lsjhxon/?utm_source=ig_tumblr_share&igshid=1ws6zkmjhkvod