BUSINESS INTELLIGENCEKS091323The most interesting tools for Business Technologies today are they that using the latest kind of technology. The more modern technology used by the tools, the better use it can be. Here we report 4 Technologies That Are Reshaping Business Intelligence, written by Doug Henschen. The next-generation BI is being formed by predictive analytics, real-time monitoring, in-memory processing, and SaaS.

Information System DepartmentFaculty of Information TechnologyINSTITUT TEKNOLOGI SEPULUH NOPEMBER

DUE DATE : 04.09.2009

SUMBISSION DATE : 04.09.2009

EXAMINED BY :

ASSIGNMENT CODE : Ass.W02ASSIGNMENT NAME : Exploring Business Intelligence Tools

PREPARED BY“A”

1. Rama Catur Andy Putra Permana 52071000772. Goeij Yong Sun 52071000893. Arief Rakhman 5207100092

Exploring Business Intelligence Tools

In this assignment, we try to find interesting development for Business Intelligence tools from intelligententerprise.com.

There are many tools for Business Technologies today. The most interesting are they that using the latest kind of technology. The more modern technology used by the tools, the better use it can be. Not only the business that shapes technology, but the technologies can shapes business, for the need of keeping competitive advantages. One article we got from the website is 4 Technologies That Are Reshaping Business Intelligence, written by Doug Henschen, published in August 2009. The full article can be viewed in http://www.intelligententerprise.com/showArticle.jhtml?articleID=219500509.

Based on the article, the next-generation BI is being formed by predictive analytics, real-time monitoring, in-memory processing, and SaaS.

Predictive Analytics

Analytics and predictive capabilities have been around for decades, but the interest is bigger today. Companies are peering more deeply into the future to get more profit. BI vendors that lacked analytic tools have rushed to integrate them into their BI suites. For example SAP BusinessObjects and IBM Cognos have integration deals with SPSS. In May, IBM launched an Analytics & Optimization practice, and then last month took the plunge with the SPSS deal.

From SAP website, we got information about SAP BusinessObjects. With SAP Businessobjects BI Solutions, we can do advanced analytics. It is designed for financial and business analysts. It have advanced analytic tools to create real-world value from the information assets. Relying on sophisticated analytic engines that can access both numeric and text data, these tools will examining complex historical data to look for trends, outliers, and patterns through a visual interface.

There are three versions of SAP BusinessObjects: SAP BusinessObjects Voyager, SAP BusinessObjects Predictive Workbench, and SAP BusinessObjects Set Analysis. The version that is using predictive analysis is SAP BusinessObjects Predictive Workbench.

GROUP

SAP BusinessObjects Predictive Workbench, based on SPSS Clementine, helps the organization reach its goals using predictive analytics. It can uncover trends and patterns to solve business problems, anticipate business changes, and gain insight using this powerful predictive analytics solution. SAP BusinessObjects Predictive Workbench works with the existing data environment and allows for efficient discovery of interesting and predictive findings.

We can then use these results with BI capabilities and share the results with users who need this insight most. It will simplify everyone's access to predictive analysis so they can take immediate action with confidence.

Other example is IBM Cognos 8 BI, which according on its official site, delivers the complete range of BI capabilities on a single service-oriented architecture (SOA).

Cognos provide the capabilities and information we need to make better decisions. Use reports, analysis, dashboards and scorecards to monitor business performance, analyze trends and measure results. A service-oriented architecture makes it easy to deploy and manage. Its key features are:

Build reports, OLAP cubes, dashboards and scorecards using all data sources.

Proven scalability to hundreds of thousands of users.

Modular deployment lets you meet immediate user needs and expand or modify as needed.

Real Time Monitoring and Analyzing

Between the extremes of rearview-mirror (historical) reporting and advanced predictive (future) analytics lies real-time monitoring. “Real time” today doesn’t mean subsecond or even subminute response. BI vendors have techniques to have a trick with the queries and data captures to get conventional data warehouse faster. Sometime it works, but it may be more troublesome and expensive than other alternatives.

Now the real real-time techniques will adopt stream processing technologies. It includes low-latency BI, faster business activity monitoring, and ultra-low-latency complex event processing. The real time systems enable a spontaneous action the users can take to respond an event. It will also have some automated response system ready.

The example use of real time monitoring and analyzing system is what Insurance.com do to keep its high-traffic e-commerce site. Insurance.com decided to monitor rate calls by state. For that, Insurance.com chooses IBM Cognos Now for monitor and viewing dashboards with the low-latency BI. IT met the monitoring need while adding alerting, escalation, and custom-graphics interfaces that the before application lacked. Insurance.com considered IT-specific tools for network monitoring, site monitoring, and performance monitoring, but that would have required a mixture of tools that didn't render a holistic view from one interface. Like most BI products, IBM Cognos Now is designed to tap into a variety of source systems and data types.

The monitoring practice is getting more interesting. One application monitors 15 variables to determine call-center agent capacity. When it spots excess capacity, the applications automatically adjusts CRM software to push leads to agents more quickly--a great example of real-time insight tied to real-time response.

The second app monitors the customer lead-to-close process and sends an alert to the designated managers if it detects performance glitches. If the condition persists, alerts escalate to higher-level executives.

Other example is from UPS. UPS decided it needed to replace a legacy application that tracked and did load balancing for as many as 50 million transactions made by visitors to UPS.com, as well as shipping requests through UPS's PC-based WorldShip application. The old system did classic rearview-mirror reporting--it collected server log data each night, and reported on transaction attempts, successes, and failures by servers the next morning. The response for complains would always be 'We'll tell you

tomorrow what we see..' and that’s not good. But now they can look at the dashboard and see right away whether it's an across-the-board problem or an isolated problem on a specific server.

UPS upgraded its Truviso deployment in April to add e-mail and text-based alerts. When managers see an alert about borderline performance, they can investigate and hopefully prevent an outage. Stream processing technologies promise to make "real time" reports, dashboards, and decision-support applications a reality.

In-Memory Processing

The third element poised to change BI is the much faster analysis that's possible using in-memory calculations. In-memory tools can quickly slice and dice large data sets without resorting to summarized data, pre-built cubes, or IT-intensive database tuning.

Products such as Spotfire (acquired by Tibco), Applix TM1 (acquired by IBM, now IBM Cognos TM1), and QlikTech were pioneers in the category, and in recent months more vendors have joined the in-memory ranks, or laid out plans to do so.

TIBCO Spotfire

The TIBCO Spotfire Enterprise Analytics platform offers a radically faster business intelligence experience and is far more adaptable to specific industry and business challenges than traditional alternatives.

Unlike traditional BI, the Spotfire Enterprise Analytic platform equips every employee to quickly discover new insights in the information they work with every day. Spotfire’s interactive, visual capabilities for data analysis empower individuals to easily see trends, patterns outliers and unanticipated relationships in data with unprecedented speed and adaptability.

Applix TM1

Applix's TM1 is a complete performance management application, delivering strategic business planning, budgeting, reporting and analytics for powering analysis of financial, operational, sales, employee and other business data. Applix customers worldwide use TM1 real-time response, adaptability and easy-to-use interfaces, and experience low total cost of ownership, and a majority realize a 100 percent return on their Applix investments within the first six months of deployment. The annual BPM Partners "Beyond the Hype" Webcast for 2006 recognized that Applix TM1 customers had the highest level of satisfaction of any of the leading BPM vendors. And according to The OLAP Survey 6, Applix continues to receive the highest ratings among the leading business intelligence vendors in:

Goal Achievement Better business decisions Fastest implementation time Faster, More Accurate Reporting Reduced IT Costs Median load/calculation time (2.9 minutes)

Development of In-memory

The power and appeal of in-memory products have grown in recent years as multicore, multithreaded, and 64-bit server technologies have become more commonplace and affordable. These hardware advances enable in-memory products to analyze the equivalent of multiple data marts or even small data warehouses in RAM. The technology also eliminates, or at least minimizes, the need for extensive data prep and performance tuning by IT. For end users, that means faster self-service BI without waiting in the IT queue.

SAP gave a jolt to in-memory approaches this spring with SAP BusinessObjects Explorer, which blends the Internet-search-style querying of its Polestar interface with the in-memory analysis of SAP's Business Warehouse Accelerator appliance. The product is available with or without the super-charging of in-memory 64-bit technology, but without it, it's an Internet-search-style querying tool. The big handicap: The in-memory version accesses data only in SAP Business Warehouse. An upgrade due this fall is expected to access myriad data sources.

SaaS (Software as a Service)

Software as a Service (SaaS, typically pronounced 'sass') is a model of software deployment whereby a provider licenses an application to customers for use as a service on demand. (Wikipedia)

Saas shows up as a solution of BI in fast, flexible, and affordable solution for Business Intelligence, which BI never had before. That is why small and mid firm can’t implement BI, because it is unaffordable. But with Saas, that problem will suppose to be solved.

SaaS-based BI vendors, with their multitenant data warehouses and industry-and application-specific data models, promise to get customers up and running within days or weeks. For example, Electronics manufacturer Vicor make a big decision about minimize time to process budgeting into eight weeks by replacing spreadsheet budgeting with use of Saas. SaaS vendor Adaptive Planning customized a data model and made an online performance management application accessible to 65 employees across the United States, Japan, and various regional sales offices. Employees were able to enter, review, and approve the 2008 budget within six weeks. It is really helpful for Vicor according to minimizing time.

Before, they used to be lucky if they can finish it within 5 months. Actually, they can get (probably) same function of web application for eliminate individual spreadsheet, recalculating, and have an easy workflow, but it is impossible to be accomplished within eight weeks.

But it is a $14 billion-a-year corporation with 134,000 employees. How about a private company with estimated sales about $500 million? Ken Harris, The CIO of health and beauty products maker Shaklee

taps SaaS wherever he can stretch his small IT staff and budget--RightNow for CRM, Omniture for Web analytics, and PivotLink for BI. The company uploads its sales and financial data into a PivotLink-hosted data warehouse each night, and employees use Web-accessible report and query tools to evaluate sales, marketing campaigns, and financial performance.

That flexibility is one reason Harris likes SaaS. What about cost? Harris says annual subscription fees aren't much more than the annual maintenance fees for on-premises BI software.

SaaS present as one solution of an expensive BI nowdays. It offers a very simple, fast, and affordable solution for firm, especially for small and mid firms, for implementation BI in a simple workflow with data model that every firms needs. With fast, flexible, and affordable -- three words never used to describe a major business intelligence deployment, Saas try to makes its mark in business Intelligence.

References

4 Technologies That Are Reshaping Business Intelligence http://www.intelligententerprise.com/showArticle.jhtml?articleID=219500509

SAP Businessobjects BI Solutions – Advanced Analyticshttp://www.sap.com/solutions/sapbusinessobjects/large/business-intelligence/advanced-analytics/index.epx

Cognos 8 Business Intelligence – Analysishttp://www-01.ibm.com/software/data/cognos/products/cognos-8-business-intelligence/analysis.html

http://www.insurance.com/

http://www.ups.com/

http://id.wikipedia.org/wiki/SaaS