business analytics

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Data Visualization Techniques From Basics to Big Data With SAS Visual Analytics

Published By: SAS     Published Date: Apr 25, 2017
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis. The heart and soul of SAS Visual Analytics is the SAS® LASR™ Analytic Server, which ca
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SAS

TDWI Checklist Report: Gaining Business Value from Governed Analytics and Discovery

Published By: SAS     Published Date: Apr 25, 2017
This TDWI Checklist provides seven steps your organization can follow to apply a balanced governance strategy as you expand your use of self-service visual analytics and discovery.
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SAS

TDWI Best Practices: Improving Data Prep for BA

Published By: SAS     Published Date: Apr 25, 2017
Organizations in pursuit of data-driven goals are seeking to extend and expand business intelligence (BI) and analytics to more users and functions. Users want to tap new data sources, including Hadoop files. However, organizations are feeling pain because as the data becomes more challenging, data preparation processes are getting longer, more complex, and more inefficient. They also demand too much IT involvement. New technology solutions and practices are providing alternatives that increase self-service data preparation, address inefficiencies, and make it easier to work with Hadoop data lakes. This report will examine organizations’ challenges with data preparation and discuss technologies and best practices for making improvements.
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SAS

The Winning Formula for Financial Services

Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them? Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
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Alteryx, Inc.

The Untapped Power of Self-Service Data Analytics

Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Data Analytics has become critical for many business decision makers. However, many of these managers and data analysts still rely on spreadsheets and other legacy-era tools that fall far short of current needs. As a result, they also rely heavily on a virtual army of data specialists and scientists, working under the auspices of a centralized analytics group, to prepare, blend, analyze, and even report on the critical data they need for decision making. Download this new paper to get the details behind self-service data analytics, and how it lets business analysts: Take charge of the entire analytical process, instead of relying on other departments Overcome limitations of legacy tools to save time and prevent errors Make more comprehensive and insightful business decisions at speed
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Alteryx, Inc.

Tech Target Editorial - Solutions Spotlight: How to optimize your MDM strategy

Published By: IBM     Published Date: Apr 18, 2017
Companies in all industries can benefit from a master data management program, advises MDM expert Anne Marie Smith. Learn how to enhance yours.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
    
IBM

The Era Of Hybrid Environments Is Here: Is Your Data Refined And Ready?

Published By: IBM     Published Date: Apr 14, 2017
Today, all consumers can obtain any piece of data at any point in time. This experience represents a significant cultural shift: the beginning of the democratization of data. However, the data landscape is increasing in complexity, with diverse data types from myriad sources residing in a mix of environments: on-premises, in the cloud or both. How can you avoid data chaos?
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
    
IBM

Magic Quadrant For Data Science Platforms

Published By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations
    
IBM

From Business Insight To Business Action

Published By: IBM     Published Date: Apr 03, 2017
Businesses today certainly do not suffer from a lack of data. Every day, they capture and consume massive amounts of information that they use to make strategic and tactical decisions. Yet organizations often lack two critical capabilities when it comes to making the right decisions for the business: the ability to make accurate predictions about the future, and to then use those predicted insights in conjunction with organizational goals to identify the best possible actions they should take. The combination of predictive analytics and decision optimization provides organizations with the ability to turn insight into action. Predictive analytics offers insights into likely scenarios by analyzing trends, patterns and relationships in data. Decision optimization prescribes best-action recommendations given an organization’s business goals and business dynamics, taking into account any tradeoffs or consequences associated with those actions.
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predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources, data optimization
    
IBM

Predictive vs. Anticipatory: Understanding the Best Analytic Approach

Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
What’s the best analytic approach for your business? As technology has evolved, so has our ability to process data at an incredible rate, making it possible to perform what has become known as Anticipatory Analytics. While still a relatively new concept, anticipatory analytics is gaining prevalence as a methodology. If you’re seeking to understand the future needs of your business before they show obvious signs, anticipatory analytics can’t be ignored. In this document, you’ll learn: • The advantages of anticipatory analytics • The key enablers of anticipatory analytics • How anticipatory can be leveraged for your business • Why anticipatory can give you first-mover advantage • When to use anticipatory or predictive analytics, based on your goals
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Dun & Bradstreet

Enterprise Analytics Case Studies

Published By: Dun & Bradstreet     Published Date: Mar 03, 2017
Stories and statistics behind successful analytics projects The adoption of analytics across the enterprise is accelerating, and with good reason. Analytics can offer a competitive advantage by helping to identify growth opportunities, circumnavigate risk and improve customer relationships. These insights are becoming crucial parts of the business strategy for executives representing a wide array of industries. Check out our latest eBook to see how some of the world’s leading companies are using analytics to meet their needs. You’ll receive diverse examples of how organizations applied the latest statistical methodologies, such as: scorecard build, regression, decision trees, machine learning and material change to uncover meaning in data. The examples represent global brands across critical industries – Financial Services, Insurance, High-Tech, Aerospace, Manufacturing and others – where analytics helped answer their most challenging questions.
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Dun & Bradstreet

The Future of Energy and Utilities - An IBM POV

Published By: IBM     Published Date: Feb 28, 2017
Energy companies are being challenged on multiple fronts. Core expectations require the delivery of safe, reliable, affordable and sustainable energy. Business models are being challenged by alternatives such as renewables and consumers demanding more sophisticated interactions through social and mobile. Energy companies need to: Disruptively innovate business processes through analytics driven operational excellence to increase agility and responsiveness, reduce operational costs and improve asset reliability Assume the role of energy integrator to optimally balance supply and demand points Deliver a 360-degree customer-of-one experience to increase customer satisfaction and loyalty, reduce costs, and improve management of energy demand
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ibm, energy & utilities, utility trends, pov, ibm pov, customer experience, sustainable energy, affordable energy
    
IBM

CGT Research Paper: Transforming Core Consumer Products Functions with Advanced Analytics

Published By: IBM     Published Date: Feb 27, 2017
Advancements in analytics have sparked renewed excitement in the consumer products (CP) industry. Maturing analytics capabilities are now delivering greater value across major CP functions including marketing, sales, merchandising, supply chain, and more. Thus helping CP companies become more consumer and customer focused in all aspects of their businesses. Read this research report conducted by 'Consumer Goods Technology' to understand how, next-gen analytics capabilities is key in unlocking a deeper understanding of customers, help create successful new products, foster brand advocates and optimize distribution channels and ultimately shape demand
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cgt, analytics, consumer goods, distribution channels, advanced analytics
    
IBM

Frost & Sullivan: Rethinking Your Contact Center - How to Engage the Modern Customer

Published By: 8x8 Inc.     Published Date: Feb 17, 2017
This Frost & Sullivan paper will outline the difficult challenges faced by all businesses—in a variety of industries and sizes—in creating an exceptional customer experience; discuss the value of a contact center that also supports all channels of choice, disaster recovery, data analytics, and leveraging back-office workers; stress the need for cultural change throughout the organization to truly meet today’s customers’ expectations; and offer best practices recommendations for taking the lead in creating a customer journey that engenders loyalty, delivers total satisfaction, and drives revenues.
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frost & sullivan, contact center, customer engagement, cloud, culture gap, scalability, omnichannel, digital tranformation
    
8x8 Inc.

The Threat Lifecycle Management Framework

Published By: LogRhythm     Published Date: Feb 07, 2017
Globally, sophisticated cyber-attacks are compromising organizations at an unprecedented rate and with devastating consequences. Modern attackers, including criminal organizations, ideological groups, nation states and other advanced threat actors are motivated by a wide range of objectives that include financial gain, industrial espionage, cyber-warfare, and terrorism.
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security, technology, best practices, information technology, business analytics, business management
    
LogRhythm

The Forrester Total Economic Impact Of SAP Business Objects Analytics

Published By: SAP     Published Date: Feb 03, 2017
To better understand the benefits, costs, and risks associated with implementation of SAP Business Objects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to provide the conclusions of this cost and benefit analysis.
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SAP

The Total Economic Impact Of SAP Business Objects Analytics Key Findings

Published By: SAP     Published Date: Feb 03, 2017
To better understand the benefits, costs, and risks associated with implementation of SAP BusinessObjects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to report cost and benefit findings
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SAP

Supercharge Your Business Applications with Spatial Analytics from SAP HANA

Published By: SAP     Published Date: Feb 03, 2017
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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SAP

Data & Analytics Maturity Model & Business Impact

Published By: Microsoft     Published Date: Feb 02, 2017
Download the Keystone Research whitepaper to see how top performing enterprises use their IT investments to store, process, and use data to make more effective, real-time decisions. Keystone Research, a global economics and data-driven strategy consulting firm, interviewed senior IT and business decision makers at over three hundred businesses to uncover the relationship between Data & Analytics technologies and business performance. This research shows that companies who have developed the most sophisticated Data & Analytics platforms and apply these capabilities as a regular part of their business enjoy operating margins that are eight percentage points higher than lagging organizations. This translates to $100 million in operating profits on average for the more advanced companies in the sample controlling for factors such as company size and industry vertical.
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Microsoft

Addressing customer analytics with effective data matching

Published By: IBM     Published Date: Jan 27, 2017
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
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IBM

Just the facts: Four critical concepts for planning the logical data warehouse

Published By: IBM     Published Date: Jan 27, 2017
While any number of reasons can prompt a change in data warehouse solutions, there are four key facts you need to know to help you make the right choice: 1. Complexity stifles business 2. Speed is business-friendly 3. Cost reduction is crucial 4. Analytics: The key to current and future success This e-book will explore those facts and explain why they are essential when evaluating your data warehouse options.
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IBM

IBM Cognos Analytics: Converged and Governed Analytics for the Masses

Published By: IBM     Published Date: Jan 27, 2017
Learn to evaluate avenues best with democratized yet trusted analytic insights using IBM Cognos Analytics for your business decisions here.
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ibm, analytics, business intelligence, data, converged analytics, governed analytics, data management
    
IBM

From Business Insight to Business Action

Published By: IBM     Published Date: Jan 18, 2017
The synergy between predictive analytics and decision optimization is critical to good decision making. Predictive analytics offers insights into likely future scenarios, and decision optimization prescribes best-action recommendations for how to respond to those scenarios given your business goals, business dynamics, and potential tradeoffs or consequences. Together, predictive analytics and decision optimization provide organizations with the ability to turn insight into action—and action into positive outcomes. In this white paper, you’ll gain a better understanding of: The difference between predictive and prescriptive analytics How predictive and prescriptive actions complement one another to help you achieve optimized business decisions IBM’s approach to creating a powerful end-to-end decision management system
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ibm, predictive analytics, decision optimization, synergy, decision making, business goals, prescriptive analytics, decision management
    
IBM

Seven Reasons You Need Predictive Analytics Today

Published By: IBM     Published Date: Jan 18, 2017
Predictive analytics has come of age. Organizations that want to build and sustain competitive advantage now consider this technology to be a core practice. In this white paper, author Eric Siegel, PhD, founder of Predictive Analytics World, reveals seven strategic objectives that can only be fully achieved with predictive analytics. Read this paper to learn how your organization can more effectively: Compete – Secure the most powerful and unique competitive stronghold Grow – Increase sales and retain customers competitively Enforce – Maintain business integrity by managing fraud Improve – Advance your core business capacity competitively Satisfy – Meet today's escalating consumer expectations Learn – Employ today's most advanced analytics ....and finally, render your business intelligence and analytics actionable.
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predictive analytics, increase sales, customer retention, fraud management, consumer expectations
    
IBM

Finance: The new ‘champion’ for applied analytics

Published By: Oracle     Published Date: Jan 12, 2017
Businesses today expect finance to play an extended role across departments, including IT, human resources, compliance, operations, sales, marketing, and most importantly, corporate strategy.To successfully deliver on this role, the finance function needs to play a bigger and visible role in real-time decision making and continuous planning. This report explores how, using cloud and analytics, finance leaders can leapfrog a few generations of technology and offer mature analytical feature/functionality and skills to the entire organization.
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Oracle
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