Centrum Wiedzy - Analityka
Recent Analytics Insights
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4 strategies that will change your approach to fraud detectionAs fraudulent activity grows and fighting fraud becomes more costly, financial institutions are turning to anti-fraud technology to build better arsenals for fraud detection. Discover four ways to improve your organization's risk posture.
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Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests these 10 questions as a guide.
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Analytics tackles the scourge of human traffickingVictims of human trafficking are all around us. From forced labor to sex work, modern-day slavery thrives in the shadows. Learn why organizations are turning to AI and big data analytics to unveil these crimes and change future trajectories.
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Analytics: A must-have tool for leading the fight on prescription and illicit drug addictionStates and MFCUs now have the analytics tools they need to change the trajectory of the opioid crisis by analyzing data and predicting trouble spots – whether in patients, prescribers, distributors or manufacturers. The OIG Toolkit with free SAS® programming code makes that possible.
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Viking transforms its analytics strategy using SAS® Viya® on AzureViking is going all-in on cloud-based analytics to stay competitive and meet customer needs. The retailer's digital transformation are designed to optimize processes and boost customer loyalty and revenue across channels.
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Detect and prevent banking application fraudCredit fraud often starts with a falsified application. That’s why it’s important to use analytics starting at the entrance point. Learn how analytics and machine learning can detect fraud at the point of application by recognizing the biggest challenge – synthetic identities.
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Public health infrastructure desperately needs modernizationPublic health agencies must flex to longitudinal health crises and acute emergencies – from natural disasters like hurricanes to events like a pandemic. To be prepared, public health infrastructure must be modernized to support connectivity, real-time data exchanges, analytics and visualization.
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SAS CIO: Why leaders must cultivate curiosity in 2021With the change we’re all facing this year, CIOs should be counting on curiosity to play a crucial role in how we’re going to meet the challenges that lie ahead. From the moment COVID-19 hit, our IT organization has relied on curiosity – that strong desire to explore, learn, know - to fuel the urgent changes required. And it’s curiosity that will enable us to meet the needs of the future of work post-pandemic.
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Load Forecasting: Ensuring supply meets energy demandLoad forecasting helps energy suppliers meet demand for residential and commercial customers. As renewable energy resources increase, the necessity for a technology platform that adapts to load forecasting requirements becomes crucial.
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Five ways your organization can enhance resilience for years to comeInnovation, agility and customer-centricity frequently top the list of companies’ strategic objectives, and now the most urgent priority is resilience. Given this new urgency, it’s worth taking a close look at the underpinnings of resilience and how they could be applied in any industry. This article explores how analytics can help boost resilience and includes key elements to keep your organization resilient.
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Resilience in the face of unpredictabilityUnpredictability can “shatter and reshape” a society. And in these unpredictable times, it is important to remain resilient and be prepared to bounce back. This article explores what it truly means to be resilient, how to build it, and how analytics can help you act when your resilience is tested.
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Homelessness data holds insights to a hidden problemSAS partnered with The Carying Place, an organization that supports working homeless families, to find new ways to measure indicators of participant success and provide families the help they deserve.
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Finding COVID-19 answers with data and analyticsLearn how data plays a role in optimizing hospital resources, understanding disease spread, supply chain forecasting and scientific discoveries.
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How health care leaders deployed analytics when crisis hitDuring the COVID-19 pandemic, some health care providers were well-positioned to respond to rapid changes in demand. The factor that most distinguished them was that they already had a strong capacity in place for using data to inform decisions. Read about three key takeaways from their experiences.
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Situational awareness guides our responses – routine to crisisMany circumstances call for situational awareness – that is, being mindful of what’s present and happening around you. The COVID-19 pandemic heightened this need, as leaders across industries used analytics and visualization to gain real-time situational awareness and respond with fast, critical decisions.
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A data scientist’s views on data literacyGet a data scientist and teacher's perspective on the value of having foundational knowledge so you can more easily tell data fact from data fiction.
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Respond, recover and reimagineDisruptions to our lives happen regularly, though most are not as far-reaching as the COVID-19 pandemic. Whatever their nature, it’s helpful to have a plan for how to exit disruption still on your feet and in the game. Learn about the three-phase approach SAS recommends for mitigating widespread disturbances.
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Contact tracing investigations for public health: Technology enhances epidemic investigationWhat was once a cumbersome process that relied on an individual’s often incomplete or inaccurate memory, contact tracing investigations for public health has entered the digital era thanks to advanced analytics and data visualization.
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From living on the streets to owning a profitable businessZoe Empowers, a ministry for vulnerable children living in life-threatening poverty in Africa and India, finally found a way to measure and reveal its incredible impact. Using SAS, they developed an "empowerment index" that measures improvements in housing, health, education and more for program participants.
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Saving lives during a global pandemic through medical resource optimizationCleveland Clinic is operationalizing analytics to combat COVID-19, creating innovative models that help forecast patient volume, bed capacity, medical equipment availability and more.
Analityka - wprowadzenie
- Wprowadzenie
- Analityka Big Data
- Data Mining
- Analityka Predykcyjna
- Analiza Statystyczna
- Blockchain
- Neural Networks
- Data Science
- Algorithm
Analytics
If you're reading this, you probably know at least a little – maybe even a lot – about analytics. According to Wikipedia, analytics is "the discovery and communication of meaningful patterns in data." Seems obvious, right? Where the real story with analytics lies, however, is in what you can do with it. Think in terms of possibilities. Opportunities. Discoveries. Made possible by technological advancements in analytics that were never even dreamed of not so very long ago, within your lifetime. So let's explore the topic of analytics together. We'll share insights from the brightest minds in analytics – insights that you can turn into ... well, it's up to you.
Big Data Analytics
As data floods your organization on a daily basis, the question is no longer "What is big data?" Instead, it's "What can we do with the big data we have?" The answer, of course, is integral to the future of your business. And big data analytics opens up the world of the possible. With big data analytics, you can implement data mining, predictive analytics, text mining, forecasting and optimization to explore your options and make the best possible business decisions.
Data Mining
Czy słyszałeś o sprzedawcy, który zorientował się, że pieluchy i piwo są często kupowane razem? Czy jesteś świadomy, że firma, która świadczy Ci usługi telekomunikacyjne potrafi przewidzieć, czy w niedługim czasie zrezygnujesz z jej usług i zmienisz operatora, opierając się na informacjach o tym, jak wielu z Twoich znajomych już to zrobiło? Aby odkryć ukryte powiązania i zależności te przedsiębiorstwa wykorzystują technologie data mining. Jakie sekrety kryją rozrastające się repozytoria danych w Twojej firmie? Wykorzystaj technologię data mining, aby się przekonać
Predictive Analytics
So you’ve embraced the power of collecting and analyzing data. That’s a great first step, but it just scratches the surface. To get the most out of your data, you need to anticipate the future, not just analyze the past.
Whether you want to attract new customers, assess payment risk, identify fraud or forecast energy demand, predictive analytics can provide answers to your most complex questions.
Statistical Analysis
Statistical analysis isn’t just for sports geeks and political pollsters. Every day, statistics plays a critical role in informing public policy and improving human welfare. The field of statistics has grown from sampling populations to analyzing even the biggest of big data sources.
Today’s statisticians are tracking endangered species, improving agricultural processes and predicting the best treatments for complex diseases. There's a lot going on with this influential field and the statistical programming techniques used by today’s statisticians.
Blockchain
What can you store in blockchain besides Bitcoin transactions? Insurance claims, medical records and even voting records can all be stored in blockchain. Simply put, blockchain is a distributed data architecture that stores data and transactions – and validates the accuracy of those transactions by consensus. Learn more about blockchain and how you can analyze blockchain data.
Neural Networks
Neural networks are computer programs designed to imitate how the human brain learns and searches for patterns. Often referred to as artificial neural networks (ANNs), they are ideally suited to solving real-world problems in different fields. Much like a human brain, they can be trained over time to improve their interpretations of data.
Data Science
Data science is a multidisciplinary field that broadly describes the use of data to generate insight. Unlike more specialized data-related fields, such as data mining or data engineering, data science encompasses the complete life cycle of translating raw data into usable information and applying it for productive ends in a wide variety of applications.
Algorithm
An algorithm is a list of step-by-step instructions designed to accomplish a specific task or solve a specific problem. When you think about it this way, algorithms are pervasive. A French onion soup recipe, for example, is an algorithm. Combine these inputs to generate an output. Algorithms basically work the same way with computers. Whether they’re converting binary numbers into letters so you can read what’s on your tablet screen or recommending stocks based on your risk tolerance, algorithms are fundamental in modern computing. This page will focus on computer algorithms.
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