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cezarovidiu

What is business intelligence (BI)? - Definition from WhatIs.com - 0 views

  • Business intelligence is a data analysis process aimed at boosting business performance by helping corporate executives and other end users make more informed decisions.
  • Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help corporate executives, business managers and other end users make more informed business decisions.
  • BI encompasses a variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards and data visualizations to make the analytical results available to corporate decision makers as well as operational workers.
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  • The potential benefits of business intelligence programs include accelerating and improving decision making; optimizing internal business processes; increasing operational efficiency; driving new revenues; and gaining competitive advantages over business rivals. BI systems can also help companies identify market trends and spot business problems that need to be addressed.
  • BI data can include historical information, as well as new data gathered from source systems as it is generated, enabling BI analysis to support both strategic and tactical decision-making processes.
  • BI programs can also incorporate forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical analysis and big data analytics.
  • In many cases though, advanced analytics projects are conducted and managed by separate teams of data scientists, statisticians, predictive modelers and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.
  • Business intelligence data typically is stored in a data warehouse or smaller data marts that hold subsets of a company's information. In addition, Hadoop systems are increasingly being used within BI architectures as repositories or landing pads for BI and analytics data, especially for unstructured data, log files, sensor data and other types of big data. Before it's used in BI applications, raw data from different source systems must be integrated, consolidated and cleansed using data integration and data quality tools to ensure that users are analyzing accurate and consistent information.
  • In addition to BI managers, business intelligence teams generally include a mix of BI architects, BI developers, business analysts and data management professionals; business users often are also included to represent the business side and make sure its needs are met in the BI development process.
  • To help with that, a growing number of organizations are replacing traditional waterfall development with Agile BI and data warehousing approaches that use Agile software development techniques to break up BI projects into small chunks and deliver new functionality to end users on an incremental and iterative basis.
  • consultant Howard Dresner is credited with first proposing it in 1989 as an umbrella category for applying data analysis techniques to support business decision-making processes.
  • Business intelligence is sometimes used interchangeably with business analytics; in other cases, business analytics is used either more narrowly to refer to advanced data analytics or more broadly to include both BI and advanced analytics.
cezarovidiu

Magic Quadrant for Sales Force Automation - 0 views

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    "Market Definition/Description Sales force automation (SFA) applications support the automation of sales activities, processes and administrative responsibilities for B2B organizations' sales professionals. Core functionalities include account, contact and opportunity management. Additional add-on capabilities focus on improving the sales effectiveness of salespeople, such as sales configuration, guided selling, proposal generation and content management, and sales performance management support, including incentive compensation, quota, sales coaching and territory management."
cezarovidiu

PowerPivot, Power View and Inquire availability - the definitive Microsoft answer - 0 views

  • With their inclusion in Excel standalone, at a cost of less than £100, any financial barrier to obtaining the benefit of these features is greatly reduced.
  • Excel 2013 Standalone Volume License and Standalone Retail 32-bit and 64-bit.
  • PowerPivot and the two new add-ins - PowerView and Inquire, are only available on certain SKUs (versions). These include:
cezarovidiu

Entity Attribute Value in Magento - Magento tutorial lesson 19 - Magento - 0 views

  • Entity Attribute Value
  • number of attributes (properties and parameters) which can be used to describe them are potentially vast, but the number of attributes which will actually apply to a given entity are relatively modest.
  • sparse matrix
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  • vertical database
  • open schema
  • more complex queries
  • Entity: The entity represents Magento data items
  • Attribute: The attributes represent data items that belong to an entity.
  • Value: The value is the simplest to understand as it is simply a value linked to an attribute
  • 1.1. What is Entity Attribute Value
  • 1.2. Entity table structure
  • At the very least, the attribute definitions table would contain the following columns: an attribute ID, attribute name, description, data type, and columns assisting input validation, e.g., maximum string length and regular expression, set of permissible values, etc.
  • The attribute or parameter:
  • The entity
cezarovidiu

Using the JDBC Connectivity Layer in Oracle Warehouse Builder - 0 views

  • For example, suppose you want to add support for MySQL. (As of OWB 11g R2, MySQL is not on the list of supported by default platforms.) All you need to do, though, is download the MySQL JDBC driver to put it into the OWB_HOME/owb/lib/ext directory, and add the platform definition for MySQL via a Tcl script that you can run from the OMB Plus console. The contents of such a script is beyond the scope of this article. However, if you want to look at one, check out this post by David Allan, where you’ll find a detailed example of how you can add support for MySQL to Oracle Warehouse Builder 11g Release 2. Also, there is a whitepaper on OTN called the "OWB Platform and Application Adapter Extensibility Cookbook", which goes into more depth than David’s post.
cezarovidiu

Don't have a big data strategy yet? Good! | ZDNet - 0 views

  • Business Intelligence And Big Data, Q4 2012 survey of 634 BI users and planners, we found that social and mobile data is actually a pretty low priority: While big data technologies like Hadoop can definitely deal with over-hyped new data like mobile and social, the broad demand is simply not there yet. Instead we find leaders recognize that the big deal about big data is the potential for getting more value more quickly from more data, at a lower cost and with greater agility; and it is a whole range of technologies and new techniques that make more possible.
cezarovidiu

Business Intelligence | Business Intelligence.ro - 0 views

  • Dezvoltarea afacerilor aduce cu sine întrebări din ce în ce mai complexe: care este cel mai profitabil produs pe care îl vând? Care este evoluţia marjei mele de profit pe produsul X de-a lungul ultimilor ani? Cum pot fi reduse eficient cheltuielile operaţionale fără a afecta performanţa afacerii? Cum pot fi reduse pierderile pe lanţul de aprovizionare sau pe circuitul de producţie? Care este volumul de afaceri pe care îl fac cu furnizorul Y şi ce discount aş putea solicita în perioada următoare? Care este cel mai performant vânzător al meu? etc…
  • Sigur, răspunsuri la întrebări complexe pot fi obţinute şi fără aportul soluţiilor de „business intelligence” insă de cele mai multe ori obţinerea rezultatelor dorite presupune cel puţin: personal specializat (analişti), inevitabila eroare umană şi mai ales timp. Timp petrecut cu activităţi repetitive de extragere a datelor, de formatare a acestora, de definire a diverselor formule şi calcule necesare etc. Mai mult decât atât, datele odată extrase din sistemul de gestiune şi „împrăştiate” la diverse nivele din organizaţie (sub forma de fişiere text, Excel sau DBF) îşi pierd proprietăţi precum integritate, acurateţe, confidenţialitate şi, poate cea mai importantă, credibilitate.
  • Alternativa? Un sistem ce poate gestiona în mod automat transformarea datelor în informaţie şi accesul la aceasta în funcţie de rolul utilizatorului în cadrul organizaţiei, în mod securizat, cu posibilitatea interacţiunii facile cu datele şi generarea de rapoarte şi analize complexe din câteva click-uri de mouse. Şi acestea sunt numai câteva din facilităţile oferite de furnizorii soluţiilor de „business intelligence”.
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  • Lista beneficiilor poate continua cu: reducerea timpilor morţi petrecuţi cu activităţile de raportare periodică (colectarea de rapoarte, consolidări şi ajustări diverse), reducerea timpului petrecut cu activităţile repetitive, reducerea rolului departamentului de IT in generarea rapoartelor propriu-zise în favoarea utilizatorului final şi, cel mai important, reducerea timpului necesar adoptării unei decizii. În condiţiile în care decizia va fi şi mai bine documentată datorită calităţii informaţiei puse la dispoziţie, vom putea vorbi în sfărşit de o organizaţie pregătită să facă faţă oricăror schimbări din piaţă indiferent cât de bruşte ar fi acestea.
cezarovidiu

Analyzing Human Data: Take a Dive to Find Out What Your Customers Really Feel - Content... - 0 views

  • What really interests me, and what I think should interest marketers, is what I’ll call signals – one of which is intent. Intent is critical because it can predict action. For example, “Is this person shopping to buy a product like my product?” “Is this person unhappy and needing some form of attention?” “Is this person about to return the product for a reason that is addressable?”
  • Sentiment is one ingredient of intent. If someone is happy, sad, angry … that can be determined via sentiment analysis technologies.
  • Many tools struggle with context.
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  • An example I hear over and over again is “thin” – good when you’re talking about electronics, but bad if you’re talking about hotel walls or the feel of hotel sheets. To do sentiment analysis correctly, you need refinement. You need customization for particular industries and business functions.
  • The market, unfortunately, is polluted with tools that claim to have sentiment abilities, but are too crude to be usable. Even with refinement (e.g., the ability to handle negators and contextual sentiment), approaches that deliver only positive and negative ratings don’t take you very far.
  • There are definitely easy, inexpensive entry points that can meet basic, just-getting-started needs: tools for social listening, survey analysis, customer service (handling contact-center notes, for instance), customer experience (via analysis of online reviews and forums), automated email processing, and other needs. These technologies are user friendly, available on demand, as a service.
  • Text mining:
  • Digital Reasoning, Luminoso and AlchemyAPI.
  • Image recognition and analysis: Image analysis now automatically identifies brand labels in pictures.
  • VisualGraph (now owned by Pinterest), Curalate, Piqora (nee Pinfluencer), and gazeMetrix.
  • Emotional analysis in images, audio, and video: These companies promote analysis of speech and facial expression primarily for structured studies
  • • Affectiva conducts webcam emotional analysis for media and ad research, including development tools to integrate emotional study in mobile apps. • Emotient performs emotional analyses in retail environments, evaluating signage, displays, and customer service. • EmoVu by Eyeris tests the engagement level of both short- and long-form video content. • Beyond Verbal studies emotion based on a person’s voice in real time.
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