SAS Forum India - SAS Visual Analytics - &#x27;Visualize This!&#x27;

This document discusses the evolution of business intelligence (BI) and analytics. It describes how BI has transitioned from using limited, pre-selected data sources to providing access to all organizational data. It also discusses how analytics have become more democratic and self-service oriented, empowering a new role of "citizen data scientist" to perform their own analytics. The document advocates challenging staff to use new BI tools over three weeks to uncover insights from all available data sources.

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The document discusses big data and big analytics. It notes that big data refers to situations where the volume, velocity, and variety of data exceeds an organization's storage and processing capabilities. It then outlines SAS's approach to high-performance analytics, including in-memory architecture, grid computing, and in-database analytics to enable real-time insights from large and diverse datasets. Several case studies demonstrate how SAS solutions have helped customers significantly reduce analytics processing times and improve outcomes.

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This document discusses and demonstrates the capabilities of SAS Visual Analytics. It describes how SAS Visual Analytics allows users to prepare, analyze, and visualize data through an easy-to-use drag-and-drop interface without programming. Key capabilities include data preparation from various sources, interactive visualization, predictive modeling, mobile access, and integration with Microsoft Office.

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Louis Fernandes

Synopsis: How SAS believes organisations can turn Big Data in to competitive advantage through the use of High Performance Analytics. In this presentations, we look at how SAS is seeing organisations take the outputs from big data analysis and turn them into tangible business outcomes through real-time decision-making. In it, we explore: - Why we believe organisations need to exploit their data assets to create the insights that build competitive advantage - How to develop infrastructures required to support multi-dimentsional insight - What SAS is doing to make this a reality Key topics include: - Data governance - Big data infrastructure - High performance analytics - Data visualisation About SAS: - World’s largest, privately held software company, - 35 years old - Focus on advanced and predictive analytics right from the word go - Big data has been in our DNA before it became mainstream

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Qlik has a perpetual license model with yearly maintenance and upgrades, while SAS VA has an annual license model. According to Gartner, SAS VA has the highest 3-year total cost of ownership. Qlik is easier for developers and end users to use, especially for creating interactive dashboards, while SAS VA is among the most difficult and time-consuming tools for content creation. Qlik supports massive data volumes through in-memory and direct discovery techniques without requiring data staging, while SAS VA also handles large data volumes.

What are the the main areas of analytics and how can they benefit your business? Learn the value of SAS analytics and how you can get better insight into your data to make more profitable decisions. By getting a better understanding of your data you will know which part of the data can be reliably forecast using time series methods and which cannot. You will also gain an understanding of any hierarchical structure in the data that can be used.

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Data is an organizations most valuable asset, but raw data by itself has little value. To drive data’s worth, it must be managed and processed to extract value and information that decision makers can leverage and turn into actionable insights. It is the ways in which a company choses to put that information to use that will determine the true value of its data. Through business intelligence and business analytic tools, businesses are enabling themselves to make more strategic, accurate decisions, while optimizing business processes. Hear from Info-Tech Research Group and learn what you need to consider when choosing an analytics solution provider. The webinar will highlight Info-Tech Research Group’s recently published vendor landscape for selecting and implementing Business Intelligence and Business Analytics solutions. The report positions SAS as the only leader across all four categories of Enterprise BI, Mid-Market BI, Enterprise BA and Mid-Market BA.

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This will be an engaging, fast-paced and informative presentation and discussion of the latest tools and trends in predictive analytics. The webinar will include a demo of the PMML capabilities in Alpine Data Labs Chorus 4.0 and instant deployment of predictive models via Zementis solutions. On this webinar you’ll come away with the following knowledge: Quickly start your very own Alpine Chorus 4.0 advanced analytics project and export to PMML with ease. Leverage the power of PMML in a simple Fraud Detection example. Operationalize your project with Zementis deployment solutions.

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Raymond Fu gave a presentation on building an enterprise analytics platform at the SoCal Data Science Conference. He has over 16 years of experience in big data, business intelligence, and enterprise architecture. He discussed how big data disrupts traditional architecture and requires new skills. Advanced analytics involves creating predictive models through machine learning to enable strategic and operational decisions. An enterprise analytics strategy involves data management, modernizing data platforms, and operationalizing advanced analytics models. Fu outlined the key capabilities needed for data management, analytics creation, and analytics operationalization. He provided examples of reference architectures and services that can be used to build an enterprise analytics platform.

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Over the past eight or nine years, applying DevOps practices to various areas of technology within business has grown in popularity and produced demonstrable results. These principles are particularly fruitful when applied to a data analytics environment. Bob Eilbacher explains how to implement a strong DevOps practice for data analysis, starting with the necessary cultural changes that must be made at the executive level and ending with an overview of potential DevOps toolchains. Bob also outlines why DevOps and disruption management go hand in hand. Topics include: - The benefits of a DevOps approach, with an emphasis on improving quality and efficiency of data analytics - Why the push for a DevOps practice needs to come from the C-suite and how it can be integrated into all levels of business - An overview of the best tools for developers, data analysts, and everyone in between, based on the business’s existing data ecosystem - The challenges that come with transforming into an analytics-driven company and how to overcome them - Practical use cases from Caserta clients This presentation was originally given by Bob at the 2017 Strata Data Conference in New York City.

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To stay relevant in a fast-changing business and data environment, business and analytics leaders need to recognize that their teams are no longer the center of the data universe. They need to reach out and partner with other data analytics players in the organization and create a shared vision for the future. The new business analytics leader fosters a rich analytical ecosystem of people, processes and technologies that fuels a data-driven organization. You Will Learn: - How the data world has changed and why - The cyclical nature of power in the data world - Characteristics of the new analytical ecosystem - The role of BI leaders and teams in the new world order

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This document discusses big data and analytics. It notes that big data refers to large volumes of both structured and unstructured data that exceed typical storage and processing capacities. Key considerations for big data and analytics include data, analytics techniques, and platforms. Trends include growth in data size and velocity, declining storage costs, and multicore processors. Common challenges in analytics involve flexible models, powerful algorithms, and effective visualization to solve large, complex business problems. The document promotes SAS's high-performance analytics approach.

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This document discusses providing technical support and training for SAS Visual Analytics. It lists the SAS Visual Analytics products that can be supported, including Hub, Explorer, Designer, Viewer, and Data Builder. It also outlines requirements for strong SAS programming and SQL knowledge, experience preparing datasets and using LASR procedures, and skills in accessing data, preparing datasets for reporting, and installing and configuring SAS Visual Analytics. Support contact is provided.

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Two of the tech industry’s essential front runners providing business intelligence solutions are Microsoft’s Power BI and Tableau. These leaders of data visualization help businesses narrow down and analyze their data with powerful built-in tools and clear visualizations. Each platform has distinctive strengths and weaknesses that should be considered before deciding on a business intelligence software. Affirma is a top Business Intelligence Consultant: http://www.affirmaconsulting.com/our-services/business-intelligence-consulting/

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Technology Strategies for Big Data Analytics,

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SAS Presentation delivered at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012 Presentation title: Technology Strategies for Big Data Analytics, by Bernard Blais, Global Strategist and Principal Manager, SAS The exploding volume, complexity and velocity of big data present an increasing challenge to organizations, but also a significant opportunity to derive valuable insights. As organizations are tasked with managing massive data sets, it’s clear that the value of big data will be derived from the analytics that can be performed on it. Analytics is the key to identifying patterns, managing risks and tackling previously unsolvable problems. This presentation provides an overview of how to comprehensively tackle big data, including emerging strategies for information management, analytics, and high performance analytics.

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SAS is a partner that is dedicated to helping companies grow. It has over 50,000 customers globally including 97 of the Fortune 100 companies. SAS is committed to advanced business analytics and has been for over 35 years. With big data and advanced analytics, SAS provides high performance analytics solutions that allow previously impossible services and applications to become possible. SAS fully utilizes parallel processing resources to perform efficient advanced analytics, allowing analysts to solve more complex business problems and integrate results into decision making.

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The Briefing Room with Mark Madsen and SQLstream Live Webcast Mar. 12, 2013 The battle cry of “time to insight” continues to change the way organizations seek insights from their data, big and small. One increasingly popular strategy focus on analyzing data streams, ranging from social media to machine-generated data captured in logs. By focusing on the kind of continuous intelligence that can flow from such analysis, organizations can stay ahead of their competitors by seizing new opportunities, and often avoiding problematic disruptions. Register for this episode of The Briefing Room to hear veteran Analyst Mark Madsen of Third Nature, as he explains how a new wave of technologies offers a compelling alternative to the traditional means for generating insights. He’ll be briefed by Damian Black of SQLStream who will explain how his company’s platform was designed to enable real-time analysis of multiple data streams. He’ll discuss how streaming analytics can remove the gap between traditional business intelligence and operational systems. Visit: http://www.insideanalysis.com

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This document discusses SAS In-Database, which allows SAS functions, models, and code to run directly inside databases. Key points include: - SAS In-Database aims to streamline analytics workflows, improve performance, and ensure data consistency. - It works by embedding SAS capabilities like scoring functions, modeling, and data preparation directly into databases. - SAS has partnered with Aster Data to enable these in-database analytics using Aster's nCluster platform.

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The document discusses SAS High-Performance Analytics, a product that leverages in-memory architecture through a dedicated software and hardware appliance to drive high-performance analytics. It highlights how the product addresses the entire analytical lifecycle from data exploration to model deployment to achieve insights at breakthrough speed. Key differentiators of the product include being the only in-memory offering that can develop and deploy high-end analytics models.

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The Briefing Room with Krish Krishnan and Teradata Live Webcast on Dec. 4, 2012 The current Holy Grail of analytical systems is the Unified Data Architecture: a management layer that connects people and systems to all the appropriate information sources, both structured and unstructured, across the entire enterprise. The idea is to provide a strategic view of information assets, ideally with an intelligent metadata layer that helps users align salient data sets, thus enabling a big-picture perspective that fosters insight, collaboration and improvement. Check out this episode of The Briefing Room to hear veteran Analyst Krish Krishnan explain why we're closer than ever to achieving this holistic perspective for data assets. He'll be briefed by Imad Birouty of Teradata, who will tout his company's Unity offering, a management environment for connecting Teradata systems of all shapes and sizes. He'll explain how Unity allows users to navigate through complex information architectures, route queries to specific data sources, even access Big Data in Hadoop via AsterSQL. Birouty will also offer a sneak peek at Shark, a new project spun out of the Kickfire acquisition, which promises super-high performance queries on specific workloads. Visit: http://www.insideanalysis.com

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This document discusses Paxata, an intelligent data preparation platform. It summarizes Paxata's history and products, and describes common data challenges that enterprises face. These include spending significant resources on manual data preparation in Excel, which can introduce errors and limit agility. The document then outlines how Paxata addresses these challenges through its self-service, visual, intelligent and collaborative data preparation capabilities. It provides examples of Paxata's use in machine learning pipelines and integration with AWS services. Customer use cases and industry analyst recognition of Paxata as a leader are also mentioned.

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Solution that delivers reporting, analysis, dashboard, planning, budgeting and forecasting capabilities at an affordable price. View the webinar video recording and download this deck: http://www.senturus.com/resources/affordable-analytics-and-planning/. Watch this webinar if you are considering switching from spreadsheets to a business analytics system and searching for an affordable, easy-to-implement solution. Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.

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