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cezarovidiu

Magic Quadrant for Business Intelligence and Analytics Platforms - 0 views

  • Integration BI infrastructure: All tools in the platform use the same security, metadata, administration, portal integration, object model and query engine, and should share the same look and feel. Metadata management: Tools should leverage the same metadata, and the tools should provide a robust way to search, capture, store, reuse and publish metadata objects, such as dimensions, hierarchies, measures, performance metrics and report layout objects. Development tools: The platform should provide a set of programmatic and visual tools, coupled with a software developer's kit for creating analytic applications, integrating them into a business process, and/or embedding them in another application. Collaboration: Enables users to share and discuss information and analytic content, and/or to manage hierarchies and metrics via discussion threads, chat and annotations.
  • Information Delivery Reporting: Provides the ability to create formatted and interactive reports, with or without parameters, with highly scalable distribution and scheduling capabilities. Dashboards: Includes the ability to publish Web-based or mobile reports with intuitive interactive displays that indicate the state of a performance metric compared with a goal or target value. Increasingly, dashboards are used to disseminate real-time data from operational applications, or in conjunction with a complex-event processing engine. Ad hoc query: Enables users to ask their own questions of the data, without relying on IT to create a report. In particular, the tools must have a robust semantic layer to enable users to navigate available data sources. Microsoft Office integration: Sometimes, Microsoft Office (particularly Excel) acts as the reporting or analytics client. In these cases, it is vital that the tool provides integration with Microsoft Office, including support for document and presentation formats, formulas, data "refreshes" and pivot tables. Advanced integration includes cell locking and write-back. Search-based BI: Applies a search index to structured and unstructured data sources and maps them into a classification structure of dimensions and measures that users can easily navigate and explore using a search interface. Mobile BI: Enables organizations to deliver analytic content to mobile devices in a publishing and/or interactive mode, and takes advantage of the mobile client's location awareness.
  • Analysis Online analytical processing (OLAP): Enables users to analyze data with fast query and calculation performance, enabling a style of analysis known as "slicing and dicing." Users are able to navigate multidimensional drill paths. They also have the ability to write back values to a proprietary database for planning and "what if" modeling purposes. This capability could span a variety of data architectures (such as relational or multidimensional) and storage architectures (such as disk-based or in-memory). Interactive visualization: Gives users the ability to display numerous aspects of the data more efficiently by using interactive pictures and charts, instead of rows and columns. Predictive modeling and data mining: Enables organizations to classify categorical variables, and to estimate continuous variables using mathematical algorithms. Scorecards: These take the metrics displayed in a dashboard a step further by applying them to a strategy map that aligns key performance indicators (KPIs) with a strategic objective. Prescriptive modeling, simulation and optimization: Supports decision making by enabling organizations to select the correct value of a variable based on a set of constraints for deterministic processes, and by modeling outcomes for stochastic processes.
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  • These capabilities enable organizations to build precise systems of classification and measurement to support decision making and improve performance. BI and analytic platforms enable companies to measure and improve the metrics that matter most to their businesses, such as sales, profits, costs, quality defects, safety incidents, customer satisfaction, on-time delivery and so on. BI and analytic platforms also enable organizations to classify the dimensions of their businesses — such as their customers, products and employees — with more granular precision. With these capabilities, marketers can better understand which customers are most likely to churn. HR managers can better understand which attributes to look for when recruiting top performers. Supply chain managers can better understand which inventory allocation levels will keep costs low without increasing out-of-stock incidents.
  • descriptive, diagnostic, predictive and prescriptive analytics
  • "descriptive"
  • diagnostic
  • data discovery vendors — such as QlikTech, Salient Management Company, Tableau Software and Tibco Spotfire — received more positive feedback than vendors offering OLAP cube and semantic-layer-based architectures.
  • Microsoft Excel users are often disaffected business BI users who are unable to conduct the analysis they want using enterprise, IT-centric tools. Since these users are the typical target users of data discovery tool vendors, Microsoft's aggressive plans to enhance Excel will likely pose an additional competitive threat beyond the mainstreaming and integration of data discovery features as part of the other leading, IT-centric enterprise platforms.
  • Building on the in-memory capabilities of PowerPivot in SQL Server 2012, Microsoft introduced a fully in-memory version of Microsoft Analysis Services cubes, based on the same data structure as PowerPivot, to address the needs of organizations that are turning to newer in-memory OLAP architectures over traditional, multidimensional OLAP architectures to support dynamic and interactive analysis of large datasets. Above-average performance ratings suggest that customers are happy with the in-memory improvements in SQL Server 2012 compared with SQL Server 2008 R2, which ranks below the survey average.
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    "Gartner defines the business intelligence (BI) and analytics platform market as a software platform that delivers 15 capabilities across three categories: integration, information delivery and analysis."
cezarovidiu

Comparing Arbitrary Time Periods in OBIEE - 0 views

  • The Ago() “time series function” can be used to show data for a  previous time period, as long as the previous time period corresponds to a level that has been defined in the period hierarchy. A typical period hierarchy containing day, month, quarter, and year levels would allow you to use the Ago function to construct measures showing data for day ago, month ago, quarter ago, year ago (or N days ago, N months ago, etc.).
cezarovidiu

Art Of BI Coverage of Business Analytics in 2013 | Art of Business Intelligence - 0 views

  • By the end of 2013, 72% of business executives will have tablets as their main means of consuming an Organization’s KPI’s and other analytics, scorecarding, etc
  • Although Roambi, and Microstrategy seem to be doing all of the right things with Mobile BI, there are several major BI Vendors that are not or there is simply room for improvement.  Also on the topic of Mobile BI, one of the barriers of 2012 was the concern for securing Mobile BI within an organization.  There has been a rise of solutions but no true standardization.  Oracle has produced their Mobile Security Tool Kit for Oracle BI and we will dive into that very soon as well (have Mac OS, will travel).
  • We hope this year to compare Oracle Endeca along with QlikView, and Spotfire to break apart the vendor specific functionality and give rise to insights on how to form successful solutions to the overall problem of self-service analysis of Big Data and traditional Data Warehouse data.
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    "By the end of 2013, 72% of business executives will have tablets as their main means of consuming an Organization's KPI's and other analytics, scorecarding, etc."
cezarovidiu

Business Intelligence Blog - The ElastiCube Chronicles - 0 views

  • SiSense’s survey finds that salaries for data professionals are on the rise across all geographies. The annual earnings of a data professional can range from an average of $55,000 USD for a data analyst to an average of $132,000 for VP Analytics. As many as 61% of the survey respondents reported higher earnings in 2012 compared to 2011, and only 12% reported lower earnings.
  • Other highlights of the survey findings include: Data professionals are highly educated. 85% of the respondents have some college degree, 39% have a Master’s degree, and 5% are Ph.D.’s. Those with doctoral degrees earn on average 65% more than those with Master’s degrees, who in turn earn 16% more than those with Bachelor’s degrees. On the job experience is even more important than education in determining salary levels. On average, professionals with ten or more years of experience earn 80% more than those with 3 years or less.
  • At the same time, the survey shows that those with 6 years or less make up as much as 59% of the data profession workforce.
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  • Most Data Professionals work in teams of up to five people. “Companies are starting to realize that Data is key to their success. The majority of them, though are not growing their Data Science teams fast enough to win. This maybe because they don’t want to or because they can’t. This is an alarming trend though and only software can come to the rescue,” noted Aziza.
cezarovidiu

Using Email to Get the Conversion (Without Stalking) | ClickZ - 0 views

  • The reality of the inbox is that people subscribe to a lot more stuff than they are committed to reading. As a result, they sift through the advertising and marketing noise to find the gems--the messages they connect with and that add value to their lives.
  • your email has to add value to your customers' lives
  • From your initial sign up process to the content and frequency of your messaging, your most important job is showing your audience that you respect the privilege of being invited into their inbox.
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  • Rule #1: Don't ask for more information than you'd personally be willing to give. Asking for too much information in an opt-in form can be a major deterrent to visitors who would otherwise be likely to sign up.
  • Make signing up as simple as possible by requiring only the bare minimum. In many cases, this means just the email address. Every field you add to your form beyond that will decrease the chances of someone filling it out.
  • Here's another tip: If you really want to convince a visitor to opt in to your communications, make it clear that the value they'll receive greatly outweighs the hassle of signing up
  • An opt-in form that says something like "Sign up for our newsletter," doesn't offer any benefit to the visitor. Give people a reason to opt-in by offering them something they'll care about, like: "Sign up for our monthly newsletter and gain instant access to our 57-page e-book on X."
  • Offers of buying guides, e-books, case studies, online videos, and instant coupons are all great incentives to test.
  • I recently welcomed two kittens into the family and we buy our supplies from Petco. As soon as I signed up for Petco's Pals Rewards program, the store proceeded to email me every single day with a new coupon offer. Can you guess what I did? Yep, I opted out. I'll still buy pet supplies from Petco, but at some point, the annoyance became greater than the value of the coupons.
  • One of the most critical steps in structuring your e-commerce email campaign is to set the publish frequency to align with the types of products you're selling and who you're selling to. At a bare minimum, segment your audience into two broad categories of current customers and prospects.
  • When you're communicating with prospective customers, offer discounts, promotions and pre-sale notifications and buying tips in your emails, to move them along the conversion path.
  • You can further segment your email list by those you send to frequently, those you send to less frequently and those you send to only sometimes.
  • You'll find your sweet spot by tracking conversions from the list, looking at the opt-out rate and by allowing your audience to manage the frequency of the communications (for example, by giving them the option to change the frequency before they opt out entirely).
  • When most people opt in to receive B2B email communications, they are at the top of the conversion funnel; the "awareness" stage. A smart B2B email campaign will then provide the right content to bring the buyer deeper into the conversion funnel, with content specific for each stage of the buying cycle.
  • Here are some ideas to get you started: Explore learning concepts that get the reader up to speed on the ideas surrounding your services, and that demonstrate your brand's unique perspective.  Dive into the ideas behind why a service like yours is so important to customers, what to look for in a company, and how your service or ideas compare to others.  Answer common questions your prospective customers have at each stage of the buying cycle and even after the purchase.
  • Don't forget you're not selling to rational people. Most of the buying decisions in a B2B environment are based on what could happen if the choice is wrong. Unlike the consumer market, where an item can be easily returned if it doesn't meet the buyer's needs, making the wrong purchase decision in the B2B arena could be extremely costly.
  • Your goal as the marketer is to arm the potential buyer with content that will reduce any fear and uncertainty about selecting your business over the competition.
  • Think of topics like, "7 Biggest Mistakes People Make When Choosing [insert your service here]" as a basis for building your case. If you have a sales team, ask them for the most common objections they hear from prospects, and create your content around the specific concerns known to be top-of-mind for many buyers.
cezarovidiu

Bossie Awards 2014: The best open source applications | InfoWorld - 0 views

  • SuiteCRM was forked from the 6.5.x branch of SugarCRM because a segment of the community felt that SugarCRM Inc. was paying too much attention to its commercial editions and dragging its feet on updating the community edition. In addition to packaging up the latest SugarCRM codebase, SuiteCRM added a number of third-party extensions, resulting in a new system that is comparable to SugarCRM Professional in terms of features and functionality.
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