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  • The hidden CosTs of sCaling searCh A Practical Guide to Anticipating and Controlling Search Costs

    3D S.

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    http://www.3ds.com http://www.3ds.com/enovia

  • © 2012 Dassault SystèmesWP EXALEAD: The Hidden Costs of Scaling Search

    foreword

    This whitepaper is intended to aid you in evaluating search and information access proposals for your organization by detailing a very important, often overlooked, cost component: scaling your search solution. Too many customers are surprised to find that almost immediately after deploying a search engine, they need to scale their platform—and that the cost of scaling can be exorbitant.

    This paper therefore: • Identifies the reasons why search needs escalate so fre-

    quently and dramatically, • Explains why scaling is often expensive, • Provides practical advice for anticipating and controlling

    costs, and • Furnishes performance benchmarks for more effectively

    making cost comparisons between solutions.

    We hope this information will aid you in developing a complete TCO forecast for your search platform, one that effectively incorporates the costs associated with scaling functionality and/or performance in addition to more easily identified direct, indirect and upgrade costs.

    we welCome Your feedbaCk

    Whatever your role—IT analyst, system administrator, application end user, business manager, security expert, or simply a curious reader—your feedback is important to us. We invite you to contact us at www.exalead.com/software with your comments, suggestions or questions.

  • © 2012 Dassault Systèmes WP EXALEAD: The Hidden Costs of Scaling Search

    Table of ConTenTs

    1. why search demands & Costs escalate………………………………………………1 1.1 Users Demand Wider Access, More Features…………….…………………………………..1 1.2 IT Discovers New Uses, Additional Value………….……..……………………………………1

    2. anticipating and Controlling Costs…………………………………………………….2

    3. forecasting demand: five rules……....……………….…………………………………2 3.1 Double Your Estimated Volume; Anticipate Double-Digit Growth……………………..2 3.2 Plan for Additional Data Sources, including the Web………………………………………3 3.3 Anticipate Demand for a Web-Style Experience, and Real Web Integration………..3 3.4 Plan for Increased Compliance Demands………………………………………………………3 3.5 Position Yourself for the Unexpected…………………………………………………………..3

    4. understanding search Types & limitations…………………………………………4 4.1 Legacy Enterprise Search Products……..….…………………………………………………...4 4.2 Search Add-Ons from Mainstream Application Providers………………………………..4 4.3 Web Search Engines Ported to the Enterprise………………………………………………….4

    5. establishing apples-to-apples Cost Comparisons…….…………………………5

    6. about eXalead CloudViewTm…….……………………………………………………...5 6.1 Dual Web/Enterprise DNA………………………………………………………………………...5 6.2 High Performance with Minimal Resources………………………………………………….5 6.3 Infinite Scaling………………………………………………………………………………………...6 6.4 True Unified Data Access……………………………………………………………………………7 6.5 Rapid Time to Market, Agile Development…………………………………………………...7

    7. CloudView benchmarks……………………………………………………………….…...7 7.1 Enterprise Search……………………………………………………………………………………..7 7.2 Business Applications……………………………………………………………………………….8 7.3 Web Applications - Online Directories…………………………………………………………9 7.4 Web Applications - Online Classifieds…………………………………………………………10

    figures

    Fig. 1: Data Volume Managed by Companies Worldwide (IDC)………………………………3 Fig. 2: CloudView Scales with Minimal Resources……………………………………………….6 Fig. 3: CloudView Scales Infinitely in Five Directions……………………………………………6 Fig. 4: Scaling with a Distributed Architecture + Commodity Hardware………………….6 Fig. 5: Transform Unstructured & Structured Data into a Single Structured Resource…7

  • WP EXALEAD: The Hidden Costs of Scaling Search © 2012 Dassault Systèmes

  • WP EXALEAD: The Hidden Costs of Scaling Search© 2012 Dassault Systèmes 1

    Information workers spend 48% of their time searching for information, with 1/3 of that time resulting in failed searches and recreated work

    1.2 iT discovers new uses, additional Value

    In addition to this user-driven escalation, IT departments of- ten discover that their search engine can provide value beyond simply locating information. They learn that search engines can be used to derive new value from existing information as- sets while adding much-needed IT agility. Specifically, these engines can be used to: • Create new, exploitable assets from unstructured content

    like email, Office documents, chat and Web pages • Increase the value of existing structured content (i.e.,

    database systems) • Provide a unified data platform for constructing agile

    business applications

    Transforming Unstructured Content into an Exploitable Asset Search engines automatically classify and categorize unstruc- tured data. Once this data is structured and indexed, it can be incorporated into business information systems and processes. Enterprises find this can provide a significant competitive advantage given that unstructured data makes up on aver- age 80% of corporate information assets, and that it contains highly valuable emotive and qualitative data.

    Increasing the Value of Structured Data Because of performance limitations (databases are optimized for storing, not accessing data), and heavy licensing and infra- structure costs, database resources are frequently under-uti- lized in the enterprise. However, when IT managers discover that index-based querying is as rich as relational database querying yet 100s of times faster and cheaper, they begin to use search engines to provide alternative access to essential database content.

    Unified Data Access for Agile Applications Unified data access is essential for meeting escalating compli- ance requirements, and for satisfying Web-savvy users’ appe- tite for fast, easy information access. However, by decoupling data from traditional application layers, enterprises are also learning that search engines can enable a new breed of ‘light’ business applications.

    1) whY searCh demands & CosTs esCalaTe

    At root, search demands and costs escalate because search works. Users are hungry for better, easier information access. In fact, IDC estimates that information workers spend 48% of their time searching for and analyzing information, with one- third of that time resulting in failed searches (and re-created work), costing organizations $28,000 per worker per year.1

    1. IDC Predictions 2009: An Economic Pressure Cooker Will Accelerate the IT Industry Transformation, IDC, 12/2008

    1.1 users demand wider access, more features

    Once enterprise search is deployed and users get a taste of unified, universal data access, demands to scale the system in functionality and performance appear almost immediately. Often, this is because organizations begin with an overly basic search solution: simple keyword searching of a finite set of resources, often HTML-centric, delivered via an appliance, hosted service or open source solution, and provided to a restricted user base.

    Even when more advanced systems are deployed, and a wider initial user base is served, users still quickly demand access to a wider range of data sources, and insist on more sophisti- cated features and functionality, such as automatic clustering and categorization, multilingual indexing, natural language querying and Web-style collaboration tools. And, of course, whatever the scope or functionality, users expect the sub- second responsiveness they’ve become accustomed to on the Internet.

  • 2WP EXALEAD: The Hidden Costs of Scaling Search © 2012 Dassault Systèmes2

    Search-Based Applications (SBAs) are fast and easy to construct and can incorporate data from any source

    Without built-in scalability, even low cost solu- tions can skyrocket to millions of dollars in just a few years

    2) anTiCipaTing and ConTrol- ling CosTs

    To avoid this unpleasant turn of events, one must better antici- pate and control costs by: • Forecasting search needs as accurately as possible and

    understanding the drivers for increased demands, while still ‘expecting the unexpected’

    • Understanding the differences between the basic types of search solutions and the scaling issues unique to each

    • Establishing baseline functional and performance criteria