Data & Analytics

Data & Analytics

    Technology Integrations

    Your data is everywhere, in hundreds of silos and systems. The best analytics connect and unite it — at speed. Alteryx natively integrates with marketing, sales, finance, service, operational applications, databases, and Big Data, whether on-premise or in the cloud.

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    Data Preparation

    Analytics projects typically require six or more data sources ― and nearly half will incorporate external data too.

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    Location Intelligence

    Analyzing customers or optimizing resources across locations requires demographic and spatial analytics ― and that means not only blending data for geospatial visualization, but enriching it too.

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    Data Discovery + Management

    The velocity of data and decision making is accelerating. It’s never been more important to create a foundation of truth and relevancy to support better, faster decisions in a governed environment.

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    BI + Visualization

    Your data flows through innumerable data cleansing, prepping, blending, and modeling steps in the analytics pipeline — all before data visualization.

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    Advanced Analytics

    Leaders accurately predict outcomes ― and apply prescriptive analytics to optimize how they take action.

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    Data Discovery & Visualization

    An ideal visualization should not only communicate clearly, but stimulate viewer engagement and attention.

    Data discovery is a user-driven process of searching for patterns or specific items in a data set. Data discovery applications use visual tools such as geographical maps, pivot-tables, and heat-maps to make the process of finding patterns or specific items rapid and intuitive. Data discovery may leverage statistical and data mining techniques to accomplish these goals.

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    Predictive Analytics

    Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events.

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    Big Data

    Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, and updating and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency, cost reduction and reduced risk.

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    Data Virtualization

    Data virtualization is any approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted or where it is physically located.

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    Operational Intelligence & Machine Data

    Operational intelligence (OI) is a category of real-time dynamic, business analytics that delivers visibility and insight into data, streaming events and business operations. Operational Intelligence solutions run queries against streaming data feeds and event data to deliver real-time analytic results as operational instructions. Operational Intelligence provides organizations the ability to make decisions and immediately act on these analytic insights, through manual or automated actions.

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    Opensource BI

    It’s impossible to imagine making good business decisions without the right information to back up the decision making process. Business intelligence (BI) tools help by making it easy to extract and understand the information that you need from the mass of business data that you collect and store. In other words, they can help turn piles of data into meaningful insights that help you run your business.

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