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سعر ومواصفات Information Management : Strategies for Gaining a Competitive Advantage with Data

  • أفضل سعر لـ Information Management : Strategies for Gaining a Competitive Advantage with Data by جوميا فى مصر هو 450 ج.م.
  • طرق الدفع المتاحة هى
    دفع عند الاستلامبطاقة ائتمانيةالدفع الاليكترونى
  • تكلفة التوصيل هى 15 ج.م., والتوصيل فى خلال 2-5 أيام
  • أول ظهور لهذا المنتج كان فى يونيو 25, 2017

المواصفات الفنية

SKU:JU030BK06W5ESNAFAMZ
المؤلف:Mcknight
الموديل:9780124080560

وصف جوميا

  • Paperback ‎- Number of Pages‎:‎ 214 pages
  • Dimensions‎:‎ 149.86 x 226.06 x 15.24mm ‎- 340.19g
  • Publication date‎:‎ 01 Jan 2015
  • Publisher‎:‎ ELSEVIER SCIENCE & TECHNOLOGY
  • Imprint‎:‎ Morgan Kaufmann Publishers In
  • Publication City/Country‎:‎ San Francisco‎,‎ United States

From the Author‎:‎ The Information Architecture To Pursue A top priority of CIOs and organizations everywhere is how to best adapt the environment to manage the information asset‎.‎ There is a plethora of available systems to throw into that equation‎.‎ The possibilities can be daunting‎.‎ *‎"‎One size fits all‎"‎ does not apply to information architecture‎.‎* Gone are the days when vendors could bring their laminated architectures to a client with credibility‎.‎ * Organizations must go forward incrementally from where they are and deliver business returns with each ‎-‎- at the quarter‎-‎,‎ not year‎-level‎,‎ turnaround‎.‎ For such an important asset‎,‎ the barometer cannot be a competitor‎'‎s environment‎.‎ Early adopters of good practices will reap the most rewards‎.‎ Following are several key actions to take to improve a company‎'‎s information architecture‎.‎ Move Key Operational Systems To In‎-Memory In‎-memory for operational systems is appropriate wherever SQL is used operationally and the performance gains of in‎-memory can be utilized‎.‎ Configurations differ‎.‎ Products like VoltDB are NewSQL systems purpose‎-built for storing data and throughput of transactional systems‎.‎ NewSQL is used today for traditional high performance applications such as capital markets data feeds‎,‎ financial trade‎,‎ telco record streams‎,‎ sensor‎-based distribution systems‎,‎ wireless‎,‎ online gaming‎,‎ fraud detection‎,‎ digital ad exchanges‎,‎ and micro transaction systems‎.‎ NewSQL systems are in‎-memory‎,‎ schema‎-based DBMS systems that scale out in a cluster‎.‎ They have high availability architectures that use synchronous‎,‎ multi‎-master‎,‎ active‎-active replication‎.‎ As the name implies‎,‎ NewSQL supports full SQL ‎- aggregate functions‎,‎ LIKE‎,‎ UNION‎,‎ materialized views‎,‎ indexes‎,‎ etc‎.‎ In‎-memory also is found in DBMS environments that primarily scale‎-up like SAP HANA‎,‎ Teradata‎,‎ and IBM PureData‎.‎ With in‎-memory systems like HANA‎,‎ a company can store its entire operational database entirely in RAM as the primary persistence layer‎.‎ With the increasing number of cores ‎(‎multi‎-core CPUs‎)‎ becoming standard‎,‎ CPUs are able to process increased data volumes in parallel‎.‎ Main memory is no longer a limited resource‎.‎ These systems recognize this and fully exploit main memory‎.‎ Caches and layers are eliminated because the entire physical database is sitting on the motherboard and is therefore in memory all the time‎.‎ By providing added performance and full ACID compliance‎,‎ these systems are pushing up the threshold of size and complexity where NoSQL systems make sense‎.‎ Selectively Utilize Data Stream Processing Data stream processing and event stream processing can hardly be considered a data store alongside DBMS and file systems since it doesn‎'‎t actually store data‎.‎ However‎,‎ it is a data processing platform‎.‎ Data is only stored in data stores for processing later anyway so if an organization can perform all processing without the storage‎,‎ it can skip the storage‎.‎ Profile data‎,‎ such as found in a Master Data Management hub can be added to the processing alongside the stream‎,‎ providing instantaneous context‎-sensitive processing in real‎-time‎.‎ Examine The Syndicated Data Marketplace Data has existed for purchase for a while‎,‎ but the data has mostly been sourced into a very specific need‎,‎ such as a marketing list for a promotion‎.‎ As organizations make the move to more widespread data access and leveragable data structures‎,‎ an investment in syndicated data can be leveraged throughout the enterprise‎.‎ Embrace Master Data Management When facing a mounting workload adding value to an enterprise with information management‎,‎ considering key components of each application that can be managed separately is wise‎.‎ The most prominent of these components is master data‎.‎ Building master data in a scalable‎,‎ sharable manner‎,‎ such as with a master data management approach‎,‎ will streamline project development time and bring consistent data to multiple applications‎.‎ Utilize Data Virtualization Dispense with the notion that each query can come from one data store‎.‎ With data virtualization making big gains in recent years‎,‎ data can be selectively stored in its best‎-fit platform and still be served to queries requiring data from elsewhere‎.‎ Data virtualization can be a way to save the day for one‎-off queries or selective queries using data virtualization can be architected into scheduled operations‎.‎ Marginalize Multidimensional Databases The hyper‎-denormalized multidimensional structure has proved a very difficult structure to use effectively‎.‎ When created ‎"‎spot on‎"‎ to a query need‎,‎ it is a good performing structure‎.‎ When mismatched due to too few columns in the structure ‎(‎requiring ‎"‎drill through‎"‎‎)‎ or too many‎,‎ creating overhead‎,‎ it becomes an encumbrance‎.‎ Use Data Warehouses Strategically The data warehouse concept is still necessary in any modern environment‎.‎ The idea of sharing the data‎,‎ the DBMS platform‎,‎ a model‎,‎ the methods‎,‎ and the tools across different data sets and subject areas brings many benefits‎.‎ Making data warehouse data columnar in orientation generally would help a data warehouse more than it would hurt‎.‎ However‎,‎ people don‎'‎t generally like any downsides with their upgrades‎.‎ A data warehouse community is not just multiple people‎.‎ It‎'‎s very disparate user groups‎.‎ The ‎"‎groupthink‎"‎ of the data warehouse also will limit finding the value proposition for the in‎-memory data warehouse although SSD storage is a must‎.‎ The data warehouse can be the lowest common denominator approach to storing data‎,‎ which is not bad for the mid‎-specification analytic workload‎.‎ Data warehouses will see evolutionary change‎,‎ but new applications and those who want specific analytic features may just source their data from the data warehouse‎.‎ There are many of these ‎"‎marts‎"‎ being built today‎.‎ The expansion of platform features in DBMS will continue as marts go searching for their best‎-fit platform‎.‎ Make Analytic Marts Columnar And In‎-Memory Analytic marts built to support a single application‎,‎ subject area‎,‎ or department are well served to optimize around the specific requirements‎.‎ These marts‎,‎ which are multiplying throughout enterprises‎,‎ have eschewed joining forces with the data warehouse‎,‎ often because the analytic features will not be turned on for the data warehouse‎.‎ At less than 5 terabytes‎,‎ analytic marts provide a great playground with little downside and bureaucracy that prevent trying out a columnar orientation and in‎-memory processing‎.‎ Once tried‎,‎ these features have quick appeal because the performance they create is often orders of magnitude greater performance for analytic processing‎.‎ Priase for Information Management‎:‎ ‎"‎This is an excerpt from the first chapter of Information Management‎:‎ Strategies for Gaining a Competitive Advantage with Data‎,‎ written by William McKnight‎.‎‎.‎‎.‎he addresses the relationship between information management and business value‎,‎ explores data management technologies‎,‎ and offers advice on maximizing the potential of enterprise information‎.‎‎"‎‎-‎-SearchDataManagement‎.‎com‎,‎ March 31‎,‎ 2014 ‎"‎‎.‎‎.‎‎.‎overall it does provide some very useful information and guidance that could be used as part of a preparation and planning exercise towards developing a suitable data and information management strategy‎.‎‎.‎‎.‎ it would make a suitable first guide for anyone who has been given the task of developing such a scheme‎,‎ and might help to clarify some of the key issues in such a way as to make the task a little bit easier‎.‎‎"‎ Score‎:‎ 7 out of 10‎-‎-BCS‎.‎org‎,‎ April 2014 ‎"‎William McKnight has delivered a very clear and concise explanation about how to get the most from your organization‎'‎s data‎.‎ He steps the reader through an assortment of data processing technologies and approaches and show which deliver the best ROI for which types of workloads‎.‎ This is a desperately needed mapping that many users will find invaluable‎!‎‎"‎‎-‎-Wayne Eckerson‎,‎ business intelligence thought leader and president of Eckerson Group‎,‎ a business‎-technology management consulting firm specializing in BI‎,‎ performance management‎,‎ and analytics‎.‎ ‎"‎A blueprint and action plan for a corporate information management strategy‎,‎ this book is a useful guide for anyone who wishes to improve business success with technology‎.‎ Author William McKnight provides the foundation and tools for information managers to set policies and programs for the improved management of information‎,‎ while addressing advances in architecture and technology principles‎.‎‎"‎‎-‎-Julie Langenkamp‎-Muenkel‎,‎ Editorial Director of Information‎-Management‎.‎com ‎"‎I always enjoy William‎'‎s writing‎,‎ especially his balance between inspiring foresight and pragmatic advice rooted in real‎-world experience‎.‎ He has skillfully shown that poise again‎:‎ with his guidance you‎'‎ll find Information Management transforms what can be a burdensome responsibility into an insightful practice‎.‎‎"‎‎-‎-Donald Farmer‎,‎ VP Product Management‎,‎ qlikview‎.‎com ‎"‎Many claim we‎'‎re in the golden age of data management‎;‎ every traditional paradigm and approach seems to have a newer‎,‎ better‎,‎ and faster alternative‎.‎ This book provides a terrific overview of the new class of technologies that must be integrated into every CIO‎'‎s technology plan‎.‎‎"‎‎-‎-Evan Levy‎,‎ Co‎-Author‎,‎ Customer Data Integration‎:‎ Reaching a Single Version of the Truth ‎"‎Big data is no longer just an IT topic‎.‎ It‎'‎s one that‎'‎s now top‎-of‎-mind for executives‎,‎ too‎.‎ William McKnight takes the increasingly knotty hairball of information management‎-its practices‎,‎ technologies‎,‎ and skills‎-and unravels it in this timely and relevant book‎.‎ A must‎-read for business and IT pros alike‎.‎‎"‎‎-‎-Jill Dyche‎,‎ SAS Vice President and author of The New IT ‎"‎I challenge any Information Management professional to not get value from this book‎.‎ William covers a range of topics‎,‎ and has so much knowledge he is able to offer usable insights across them all‎.‎ The book is unique in the way it provides such a solid grounding for anyone making architectural or process decisions in the field of information management‎,‎ and should be required reading for organizations looking to understand how newer approaches and technologies can be used to enable better decision making‎.‎‎"‎‎-‎-Michael Whitehead‎,‎ CEO and Co‎-Founder‎,‎ WhereScape Software

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