FAST TRACK YOUR ACCESS TO BIG DATA WITH ANGOSS ADVANCED ANALYTICS ON SPARK Are you drowning in Big Data? Do you lack access to your data? Are you having a hard time managing Big Data processing requirements? How are you extracting vital insights from your Big Data environments? Advanced Analytics on Spark combines the power and performance of Apache Spark and Angoss software to provide users with unprecedented access to analyze data within Big Data repositories like Hadoop HDFS, Amazon S3, Cassandra, etc. These are just some of the critical questions that arise when expanding advanced analytics business capabilities. Businesses that rely on a large-scale data set framework, like Hadoop, for distributed storage and processing, require advanced analytical tools to reveal meaningful insights about their company and customers. More importantly, the rapid growth of the predictive analytics and machine learning market, as well as the noticeable heterogeneous composition of data science teams within organizations has heightened the need for data science platforms. Recognized by industry analysts as a flexible and user-friendly platform for advanced analytics, accelerates your business analytics and eliminates costs associated with cumbersome and proprietary database warehouse appliances - without compromising data access, performance, and ease-of-use. Modern advanced analytics applications need to be equipped with big data functionality that is capable of unifying infrastructure, technology, and overcoming data access, ingestion, and discovery issues. 1
Choosing the right advanced analytics platform that integrates with your Big Data framework can be a challenging task, but one that is crucial when deploying advanced analytics across the enterprise. Handling Big Data doesn t have to be an issue. In fact, Angoss makes this task easy by combining a data access and processing framework, Spark, with Angoss data exploration, discovery, and modeling functionality in the product. is a comprehensive data science platform that is integrated with Spark technology to provide unprecedented analytics and data processing capabilities. Its in-place analysis capability on distributed data eliminates data movement and allows users to stay within their big data environments. Features In-place Analysis of Data Lakes Visual analytics for large-scale distributed data sources (Hadoop HDFS, Amazon S3, and other storage supported by Spark) Seamless Integration with Spark Scalability & Performance In-memory execution on Spark Support for large distributed datasets Deploy multiple projects in parallel Operational Efficiency Asynchronous execution Automated scheduled scoring Deploy on existing Hadoop clusters This single, fully-integrated software solution enables access to open source machine-learning libraries, Big Data technologies, collaboration and governance features, comprehensive advanced analytics functionality, and numerous deployment options allowing users to overcome challenges in Big Data ingestion, access, and results interpretation. In a nutshell, harnesses the power of big data and easily converts it to valuable insights that can help you reduce risk and costs, increase revenue and productivity, improve customer experience, and identify new business opportunities in a flash. Data Access Flexibility Load and export functions supported for Hive tables, text (CSV), Parquet, ORC, and Avro Support for object stores, distributed file systems, network shares, and other enterprise data repositories (Amazon S3, HDFS, Hive, Network File Servers, FTP Servers, Hadoop Archives, etc.) Data Mining and Predictive Modeling in a Big Data framework via Spark Manipulate data in distributed storage: Append, filter, join, aggregate, sample, create new variables, and do custom transformations 2
Angoss Advanced Analytics and Big Data Architecture Benefits Efficiently harness the power of Spark on Hadoop HDFS and other distributed storage systems with a single, fully integrated enterprise application for ever changing data needs. Accelerate analytics on large-scale distributed data with unprecedented data processing speeds. Perform advanced analytics without having to move large volumes of data from one environment to the other. Facilitate visual analytics for Hadoop with access to data within HDFS and Hive. 3
Access data sources like social media feeds transactional, IoT, and Big Data environments such as Amazon S3, Hadoop HDFS, and Teradata. Perform large-scale data analytics processes with access to open source machine learning libraries such as Spark ML, TensorFlow, Geotrellis, etc. Institutionalize knowledge and promote collaboration across heterogeneous teams of different skills and tools requirements. Reduce storage footprint, risk of data exposure and data copies using in-place analytics. Overcome population variance and avoid sampling errors using larger datasets. Eliminate challenges associated with large data sets scalability using Spark integration. Deploy multiple projects on single cluster. Deploy on commodity or virtual hardware. Reduce backup overhead with HDFS. Utilize existing Cloud Reserved Instances. Use the most common cloud services: Multi-purpose Amazon AWS and Microsoft Azure resources. Use the Spark Generic Code node integrated with Jupyter Notebook to run Python programs on Spark. Embed R and Python programs in Angoss workflows using R and Python code nodes. Automatically translate Angoss models to SAS code. Features Perform decision tree analysis, strategy development, predictive modeling, and cluster analysis on distributed data Models can be deployed and evaluated in the same Big Data environment Programming Languages Write and execute Python programs on Spark Embed custom code and invoke open source packages like Spark ML and TensorFlow directly through the Angoss workflow Capability to use Jupyter notebook for interactive editing and running code via a web browser View and copy Python code for any analytic operation Analytics on Angoss Native Datasets Access all KnowledgeSTUDIO functionality for native Angoss datasets: Data preparation and profiling, Decision Trees, Strategy Trees, predictive models, cluster analysis, market basket analysis, model evaluation, comparison, deployment, and code generation Deploy Anywhere Cloud or on-premises deployment Physical or virtual environment Cloudera & Hortonworks certified 4
Angoss Software Differentiators Fully-integrated software solution that provides businesses with access to: open source machine-learning libraries for data science in the language of Python; Big Data technologies via Apache Spark; support for all large-scale distributed data storage types accessible via Spark; collaboration and governance functionality; comprehensive advanced analytics; and numerous deployment options. The easy-to-use graphical user interface is rated to be one of the best in its category by industry analysts and users. Best-in-Class Decision Trees outperfom the competition, allow automatic and manual growing and visually display results for easy interpretation. Ensemble Trees allow you to create multiple trees in one go and combine them in a single ensemle tree model using the Random Forest, Bagging, and Boosting algorithms. Ensemble models can perform better and are less prone to overfit than individual models. Unique Strategy Trees are the first of its kind for building and deploying prescriptive strategies. Users are able to combine customer segments, scores, business rules and calculations, and apply user-defined treatments and actions in order to support decisioning and the development of business strategies, actions and optimization. Segment Viewer can be used as a qualitative assessment tool to identify candidate predictor variables for use in modeling. It displays the distribution charts of the independent variables segmented by the categories of the dependent (target) variable. This allows for easy identification of variables with markedly different distributions across the target categories. Visual Analytics via Angoss native charts, graphs and reports make every stage of the data mining process easily interpretable. The integration of Tableau visual analytics further enhances Angoss s visualization capability by providing users with access to Tableau dashboards directly from within the Angoss workflow. Workflow automation allows the users to construct data mining process flows - from data extraction and preparation to model evaluation and deployment using an intuitive drag-and-drop interface. Entire workflows and individual nodes can be easily re-run on updated or refreshed data inputs. Automatic SAS code generation for the entire project workflow or any of its stages. Accurate and stable analytical algorithms and techniques used are industry-proven methods having undergone many years of testing and validation. 5
Ease of integration into other analytical environments enables data import and export to/ from Text, Microsoft Excel, SAS, SPSS, R, and databases via ODBC. Automatic code generation for Angoss models can be deployed in other rules engines and environments. Code types include SQL, SAS, SPSS, Java, PMML, XML, and structured English code. R and Python integration allows users to embed R and Python programs in Angoss workflows. About Us Angoss is a global leader in delivering advanced analytics to businesses looking to improve performance across risk, marketing and sales. With a suite of big data analytics software solutions and consulting services, Angoss delivers powerful approaches that provide you with a competitive advantage by turning your information into actionable business decisions. Many of the world s leading organizations in financial services, insurance, retail and high tech rely on Angoss to grow revenue, increase sales productivity and improve marketing effectiveness while reducing risk and cost. Headquartered in Toronto, Canada, with offices in the United States, United Kingdom and Singapore, Angoss serves customers in over 30 countries worldwide. For more information, visit www.angoss.com. North American Headquarters Angoss Software Corporation 330 Bay Street, Suite 200 Toronto, ON M5H 2S8 Canada Tel: 416-593-1122 Fax: 416-593-5077 European Headquarters New London House, 6 London Street London EC3R 7LP UK Tel: (+44) 020 3741 9522 6