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      • Building a big data practice

        For IT solution providers, there's big money in big data. That's because data volumes are growing at staggering rates, and SMBs are discovering use cases for big data. Perhaps even better for the channel, many SMBs don't have the skills needed to carry out big data projects. Yet big data is a largely untapped opportunity for the channel. This handbook aims to help solution providers that want to build a big data practice do so, with an exploration of where the biggest opportunities lay, how to build business cases, prep staff members, stand out from competitors, as well as a look at the steps two Microsoft partners have taken to build successful big data practices.

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      • Implementing two-tier ERP with manufacturing in mind

        Manufacturers that need to extend their ERP systems to remote locations are considering smaller, lightweight ERP suites as an alternative. With a two-tier ERP system, organizations can consolidate systems and save money while increasing operational efficiency.

        This three-part guide examines the homework organizations need to do -- analyzing costs and benefits -- to make an effective, informed business case for two-tier ERP. First, SearchSAP's Todd Morrison explores the potential cost savings and deployment advantages of two-tier systems -- it will shed light on why the manufacturing industry is so bent on it. Next, Morrison looks at the options available to organizations that have decided to go ahead and implement a second-tier system. It's important to determine the best fit, and there are three to choose from. Veteran IT journalist Lauren Gibbons Paul talks to industry insiders about process improvements available to organizations not quite ready to deploy a whole new ERP system.

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      • Gaining an edge with location analytics

        Location intelligence goes beyond finding a good restaurant. In business, location intelligence technologies can boost profits and decrease costs. This handbook presents potential use cases, tips for deploying location intelligence software and advice for incorporating location intelligence and analytics capabilities into mobile applications.

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      • The dos and don'ts of social media analytics

        Businesses are realizing the value of social media when it comes to customer satisfaction, brand reputation, and trends and they’re increasingly turning to social media analytics to derive these insights. However, analyzing them effectively for maximum business benefit is not an easy task. Read this handbook for advice on developing a social media analytics strategy, maintaining a clear business purpose for the program and dealing with obstacles along the way.

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      • The Analytical Sales Team Series

        Download this e-book for information on the newest trends in advanced analytics, and how it can aid your sales efforts. Read chapters on innovative analytical sales topics, including in-memory analytics, in-database analytics, complex event processing and predictive analytics.

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      • How to set up and manage a successful business analytics program

        This e-book includes how-to advice on creating an analytics culture, setting up a business analytics program and preparing for an installation of analytics software. In addition, get tips and strategies for building up an organization's analytics skill set and supporting analytics professionals. Learn how to create a top-down emphasis on fact-based decision making, learn what types of specialized analytics skills and workers your organization will need and where to find them. Get advice on the best way to structure an analytics team within your organization. Also discover how to get corporate data ready for a comprehensive analytics program through data quality, data integration and data governance efforts.

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      • Enterprise Hadoop: Ready for prime time?

        Many vendors are pitching Hadoop as the foundation for enterprise data management environments that delivers information and insights to business users and serves as a hub for other data systems and applications. In the era of big data, the case for Hadoop is strong: Hadoop provides a cost-effective way to ingest, store and process large volumes of multi-structured data. With Hadoop, organizations can store all data in its original format and provide a system of record for the enterprise. Even more, they can bring the applications to Hadoop and process the data in place.

        But does reality square with the promise today? Are companies willing to trust their enterprise data to Hadoop? The big question is whether Hadoop is ready to support enterprise-scale, production environments where data can't be corrupted or inconsistent. Does Hadoop have adequate management, monitoring, backup, recovery and security features? What are the major gaps today and what are vendors doing to plug the holes? At what point can companies trust production computing environments to Hadoop? This report, based on a comprehensive survey of business intelligence professionals and interviews with experts in the field, addresses these questions.

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      • Ensure that big data initiatives are on the right path, right away

        Analyzing pools of big data can help organizations uncover valuable information about customers and other business insights -- but it can also turn into a wild-goose chase if the process isn't well managed. This three-part guide will benefit business intelligence and analytics managers, data scientists, business executives and other readers with real-life examples of successful big data analytics efforts and project management advice.

        To get the big data ball rolling, we first take a look at two organizations in different industries -- one in healthcare, the other in banking -- taking unique approaches to big data initiatives. The differences between the two, and reasoning behind them, will provide IT professionals with a solid understanding of how to begin the conversation of implementation. Next, analyst Rick Sherman outlines the key steps big data analytics project managers must take in order to put their programs on the right path. We close with a case study about a Time Warner Cable executive who, dissatisfied with commonplace and commandeering tools such as Hadoop and NoSQL databases, decided to treat big data technologies as a complement rather than a rule.

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      • Big data deployments: Maximizing their value, minimizing mistakes

        Big data projects are becoming more common as companies seeking a competitive edge look to take advantage of an increasing variety of information from both internal and external sources. But deploying, implementing and using big data systems and big data analytics tools can be a complex undertaking.

        This e-book will offer practical advice on managing big data deployments to IT, business intelligence and analytics teams and business executives. Individual chapters will focus on evaluating and selecting Hadoop, NoSQL databases and other big data technologies; incorporating sensor data and log files into big data applications; and creating effective analytical models as part of big data programs.

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      • Getting down to business on big data analytics

        Capturing and storing big data is one thing; reaping real business value and competitive advantages from varied collections of structured and unstructured data is the ultimate goal -- and a tougher nut to crack. This handbook provides strategic insight and practical advice on some of the key facets of managing successful big data analytics programs. It will also point to real-world examples of big data analytics in action.

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      • Get a handle on BI data quality management -- before it bites you

        Ensuring that business intelligence data is clean, accurate and consistent is crucial to the success of BI efforts; analyzing bad data will send BI users off track -- quickly. And as data volumes grow and the number of data sources that organizations are looking to analyze increases, maintaining high levels of information quality is becoming a bigger challenge for BI and IT teams.

        In this handbook, readers will find practical advice on how to effectively manage data integration and data quality processes as part of BI and data warehousing programs, including a checklist of action items for identifying and resolving BI data quality problems.

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      • The biggest obstacles of data science

        Issue 5 May 2012

        Includes:
        • BI benefits in reach for SMBs, but some effort required
        • Faster data delivery livens BI performance, user satisfaction
        • Split personalities put data scientists in play
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      • Tap into enterprise data governance for business value

        Data governance is all about managing data as a business asset and ensuring that data is accurate, consistent, integrated, timely, complete and secure. This report examines the market trends for implementing data governance. Based on data from a recent survey of 317 business intelligence professionals, IT professionals and consultants, this SearchBusinessAnalytics Benchmark Report analyzes the responses and provides trend information on the increasing executive acceptance of the importance of managing data as a corporate asset, the current status and types of data governance initiatives, data quality and data governance benefits.

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      • BI projects play key role in improving business and IT alignment

        December 2012, Volume 1, Issue 12

        Includes:
        • Mind the gap: Better IT-business alignment needed
        • Bridging IT-business divide a two-way street; BI projects can help
        • With big data out of the box, maintaining order is a must
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      • Enterprise data warehouse not dead yet

        Issue 2 February 2012

        Includes:
        • Managing multiple BI tools doesn't have to be so hard
        • Data warehouse lives on: Big data best practices include ties to EDWs
        • Data virtualization tools: Are they right for you?
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      • Using decision management solutions to improve processes and operations

        Read this paper to learn why experts from both MIT and Gartner Research, as well as decision management guru James Taylor, all agree that automation and data analysis are crucial for timely, effective decisions in today's business environments. Learn about some effective decision management solutions and how to take advantage of them in your organization.

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      • Choosing the right Hadoop platform

        Focusing on the current state of the Hadoop data management platform market, this Technology Guide provides an introduction to Hadoop and suggests criteria for selecting a Hadoop data management platform. Also included are reviews of leading Hadoop systems from a variety of vendors.

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      • Making mobile BI work: Real-world advice and strategies

        Before you dive head first into mobile business intelligence (BI), you need to know about certain pitfalls. While there's no denying that BI mobility is likely to become very prevalent in the next few years, it takes a well-executed plan to ensure that your mobile BI effort is successful. Read this handbook to learn from a three-part series of articles about building and deploying mobile BI apps from consultants and IT managers. It discusses everything from mobile BI and design and development, to how you can ensure fast performance.

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      • BI Trends + Strategies Issue 11

        Nov. 2012, Volume 1, Issue 11

        Includes:
        • Successful data stewardship framework needs solid plan, firm focus
        • Data visualizations get more advanced -- and more complicated
        • Visualizing data forces BI teams to take a deep look at corporate info
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      • Strategies for effective business intelligence reporting and analysis

        For more than two decades, business intelligence (BI) professionals have tried to shoehorn all reporting and analysis tasks into the same BI toolset and architecture, often with disappointing results. Is there a real solution? Read this e-book by Wayne Eckerson, Director of Research for TechTarget, for the answer.

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      • Designing a business intelligence framework for analytics success

        In this research report excerpt, expert Wayne Eckerson explores why big data has become a hot topic. Learn how to design a successful business intelligence framework and analytics program that allows you to make something of your data and deliver value to your organization.

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      • The value of business intelligence: Driving a more agile enterprise

        Today's business intelligence is more process- and strategy-driven than in the past, and BI is fast becoming more pervasive across the enterprise and more essential in integrated enterprise architecture. It's hard to ignore the promise of BI, but defining and quantifying ROI to the business can be a challenge. This e-book explores the value of business intelligence, including its return on investment, the pros and cons of purchasing versus custom-building a BI application and how recent trends are changing the BI landscape.

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      • A complete primer to mobile business intelligence

        Business intelligence (BI) is a natural fit for mobile devices. In this e-book, appropriate for business intelligence professionals, get a complete, accessible overview of mobile business intelligence applications from industry expert Wayne Eckerson.

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      • Best practices for buying business intelligence technology

        The BI market offers a dizzying array of technology options. From collecting organizational requirements, writing RFPs, conducting evaluations and running proof of concept projects, there is a lot involved in evaluating and buying business intelligence technology. Read on to get straightforward advice from industry analysts and expert practitioners.

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      • Finding your way with visual discovery tools

        This Benchmark Report focuses on visual discovery tools, which are self-service, in-memory analysis tools that enable business users to access and analyze data visually with minimal or no IT assistance. Power users, BI specialists and casual users are increasingly employing visual discovery for analysis, typically sharing their results in the form of interactive dashboards. This report, supported by a survey of BI professionals, defines visual discovery, looks at the business benefits of this approach, and explores the perceptions and challenges associated with visual discovery tools.

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      • Visual Discovery Tools: Market Segmentation and Product Positioning

        This report explores the market for in-memory visualization tools, which provide speed-of-thought analysis to power users and interactive departmental dashboards to casual users. Visual discovery tools straddle top-down and bottom-up approaches to business intelligence and are typically deployed more quickly and at lower cost than enterprise-centric tools.

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      • Market trends tell the future of predictive analytics deployments

        Predictive analytics employs statistical or machine-learning models to discover patterns and relationships in data, thereby enabling the prediction of future behavior or activity. Long used by credit card companies, predictive analytics -- and now self-service predictive analytics -- is making inroads in organizations of all sizes. Based on a survey of more than 3,000 IT and business professionals, this report analyzes their responses to provide information on implementation status, maturity of implementations, value and vendors of predictive analytics tools.

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      • Operational analytics: Delivering insights on the fly

        As organizations recognize the benefits of providing their employees with access to real-time data, operational analytics is gaining acceptance in the marketplace. This report examines the market trends for implementing operational analytics. Based on data from a recent survey of 622 BI professionals, users and consultants, it analyzes the responses and provides trend information on adoption rates, architecture, scope of deployment, future plans, users, vendors, benefits and challenges -- as well as the types and sources of data used for operational analytics.

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      • Predictive analytics in action: Real-world examples and advice

        Predictive analytics tools can help businesses look ahead to the future, for improved decision-making and competitive advantage over rivals.  However, if your organization is looking to deploy this kind of advanced-level analytics, you will need to make sure you have the right level of analytics skills to avoid pitfalls and keep costs down. This expert handbook details everything you need to know about beginning a predictive analytics endeavor. Learn key steps for developing and implementing a predictive analytics program, expert first-hand lessons for building an analytics team, and the importance of proper skills and training for a successful program implementation.

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      • What predictive analytics pros don't do

        Issue 9, September 2012

        Includes:
        • Business intelligence manager bears burden as myths curb BI success
        • Top five things business intelligence and analytics pros overlook
        • Why execs should heed need for data governance
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      • Pushing the performance envelope with real-time BI

        There are many benefits of real-time analytics and BI tools, as they can help companies improve the efficiency and efficacy of decision-making.  However, like implementing any analytics system, the right tools need to be in place in order to maximize productivity and limit complications. This expert handbook provides practical advice for evaluating, planning, and managing deployment of real-time analytics systems. Read more about the business case for real-time BI, the benefits and challenges of incorporating pools of big data into your systems, and best practics for tackling real-time projects.

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      • Best practices for delivering real-time business intelligence analytics

        In this e-book, you'll get an overview of real-time business intelligence analytics and the best of today's options. Plus, read expert insight and advice on planning and executing a real-time BI strategy.

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      • BI research benchmark report: BI in the cloud

        With adoption of cloud BI services hovering at 33% for the past few years, this report examines the market trends for implementing cloud business intelligence. Based on data from two surveys of BI professionals, BI users or sponsors and BI consultants, this report analyzes the responses and provides trend information on adoption rates, architecture, cloud BI usage and users -- as well as the drivers and challenges facing cloud BI implementations. The report concludes with six recommendations to help identify the best approach for implementing cloud BI.

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      • Secrets of successful self-service BI

        In today's fast-paced atmosphere, consumers want their information to be available instantly, and self-service BI opens a whole new world of possibilities. View this handbook to learn more about self-service business intelligence, including how you can give business users easy-to-use BI tools and let them complete their own data analysis and reports. Find out how you can empower today's business intelligence teams with the use of self-service applications by reading this valuable resource.

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      • Collaborative BI sets stage for collective user action

        Issue 7, July 2012

        Includes:
        • Mission impossible? Data governance process takes on 'big data'
        • Collaborative business intelligence brings users together on BI
        • Location intelligence finds its way into BI processes
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      • Tips on evaluating, deploying and managing in-memory analytics tools

        Interested in running queries against data stored in a computer's memory? Read this e-book to learn about in-memory analytics technology and how it can provide much faster analytical performance than traditional business intelligence (BI) tools. Before diving into this type of data analytics, you'll want to read the valuable knowledge and expert advice gathered here.

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Featured E-ZINES on searchBusinessAnalytics.comView all >>

  • Business Information

    Cloud computing, mobile devices and massive amounts of data flowing into organizations are combining to put heavy pressure on business systems. To adapt, organizations have been forced to transform the way in which corporate information is managed.

  • BI Trends + Strategies

    BI Trends + Strategies offers best practice advice and real-world case studies to help you keep pace with the rapidly-changing business intelligence (BI), analytics and data warehousing technology landscape.

ALL TECHTARGET E-ZINES

Featured E-BOOKS on searchBusinessAnalytics.comView all >>

  • Enterprise Hadoop: Ready for prime time?

    Many vendors are pitching Hadoop as the foundation for enterprise data management environments that delivers information and insights to business users and serves as a hub for other data systems and applications. In the era of big data, the case for Hadoop is strong: Hadoop provides a cost-effective way to ingest, store and process large volumes of multi-structured data. With Hadoop, organizations can store all data in its original format and provide a system of record for the enterprise. Even more, they can bring the applications to Hadoop and process the data in place.

    But does reality square with the promise today? Are companies willing to trust their enterprise data to Hadoop? The big question is whether Hadoop is ready to support enterprise-scale, production environments where data can't be corrupted or inconsistent. Does Hadoop have adequate management, monitoring, backup, recovery and security features? What are the major gaps today and what are vendors doing to plug the holes? At what point can companies trust production computing environments to Hadoop? This report, based on a comprehensive survey of business intelligence professionals and interviews with experts in the field, addresses these questions.

  • Overcome today's disaster recovery challenges

    The use of devices not connected to a local network is a challenge for IT staffs tasked with protecting data on those devices. Completing backups within a reasonable timeframe has become an issue for organizations. Some organizations are opting for alternatives to traditional backup to address these challenges. The cloud has been pushed as an alternative to tape for offsite storage for disaster recovery. However, there are challenges with this approach and with protecting applications running in the cloud.

OTHER FEATURED E-BOOKS

Featured E-HANDBOOKS on searchBusinessAnalytics.comView all >>

  • Building a big data practice

    For IT solution providers, there's big money in big data. That's because data volumes are growing at staggering rates, and SMBs are discovering use cases for big data. Perhaps even better for the channel, many SMBs don't have the skills needed to carry out big data projects. Yet big data is a largely untapped opportunity for the channel. This handbook aims to help solution providers that want to build a big data practice do so, with an exploration of where the biggest opportunities lay, how to build business cases, prep staff members, stand out from competitors, as well as a look at the steps two Microsoft partners have taken to build successful big data practices.

  • Implementing two-tier ERP with manufacturing in mind

    Manufacturers that need to extend their ERP systems to remote locations are considering smaller, lightweight ERP suites as an alternative. With a two-tier ERP system, organizations can consolidate systems and save money while increasing operational efficiency.

    This three-part guide examines the homework organizations need to do -- analyzing costs and benefits -- to make an effective, informed business case for two-tier ERP. First, SearchSAP's Todd Morrison explores the potential cost savings and deployment advantages of two-tier systems -- it will shed light on why the manufacturing industry is so bent on it. Next, Morrison looks at the options available to organizations that have decided to go ahead and implement a second-tier system. It's important to determine the best fit, and there are three to choose from. Veteran IT journalist Lauren Gibbons Paul talks to industry insiders about process improvements available to organizations not quite ready to deploy a whole new ERP system.

OTHER FEATURED E-HANDBOOKS