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COG-706 exam Dumps Source : IBM Cognos Financial Statement Reporting Developer
Test Code : COG-706
Test Name : IBM Cognos Financial Statement Reporting Developer
Vendor Name : IBM
Q&A : 60 Real Questions
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IBM IBM Cognos Financial Statement
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established company clients now empowered with self-provider records education capabilities that pressure extra informed, strategic enterprise decisions
BEDFORD, Mass., can also 10, 2016 (GLOBE NEWSWIRE) -- Datawatch enterprise (NASDAQ-CM: DWCH) nowadays announced the immediate availability of Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics. past this 12 months, Datawatch published that IBM (NYSE: IBM) would resell Datawatch Monarch to deliver stronger and sooner records access and self-service facts education (prep) to its clients. starting today, these users can leverage Monarch to prep less, analyze more and harness the power of IBM`s cognitive computing capabilities across the widest variety of statistics sources.
records that provides the most analytical price has traditionally been locked away in prior to now inaccessible multi-structured and unstructured documents, comparable to text reviews, internet pages, PDFs, JSON and log data. And, in lots of situations, a company`s source records is distinct and rarely presents itself in an analysis-in a position format. consequently, hours are spent on guide records retrieval and prep procedures.
The Datawatch Monarch self-service records prep answer allows for facts analysts and generic business users to impulsively entry, manipulate and blend facts from just about any source. information can then be prepared for evaluation in Watson Analytics and Cognos Analytics in a fraction of the time that it takes the use of spreadsheets and other manually-intensive measures.
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IBM VisionDan Potter, Datawatch`s chief advertising officer, is scheduled to present on new advances in self-carrier information prep at the upcoming IBM vision conference in Orlando, Florida. Potter will discuss how self-provider statistics prep allows for users, mainly those in economic and operational efficiency management, to leverage a much broader range of information, and reap quicker and extra correct results. He`ll also display how an optimized records file may also be organized for direct import into Watson Analytics and Cognos Analytics. Potter`s session will take location on Wednesday, may additionally eleven, at eleven a.m. ET.
To be trained greater about Datawatch Monarch for Watson Analytics and Cognos Analytics, go to: http://www.datawatch.com/ibm-analytics.
About Datawatch CorporationDatawatch company (NASDAQ-CM: DWCH) allows for normal clients to achieve impressive consequences with their facts. best Datawatch can unlock statistics from the widest diversity of sources and prepare it for use in visualization and analytics equipment, or for different enterprise processes. When precise-time visibility into impulsively altering facts is crucial, Datawatch also enables users to investigate streaming facts, even within the most worrying environments, comparable to capital markets. businesses of all sizes in more than one hundred nations worldwide use Datawatch products, including 93 of the Fortune 100. The enterprise is headquartered in Bedford, Massachusetts, with workplaces in manhattan, London, Frankfurt, Stockholm, Singapore and Manila. To be trained greater about Datawatch or down load a free version of its business application, please discuss with: www.datawatch.com.
safe Harbor statement beneath the inner most Securities Litigation Reform Act of 1995Any statements contained during this press liberate that do not describe historic records can also constitute ahead-looking statements as that time period is defined in the deepest Securities Litigation Reform Act of 1995. any such statements contained herein, including but no longer confined to these concerning product performance and viability, are in response to existing expectations, but are discipline to a number of risks and uncertainties that can cause specific results to differ materially from expectations. The elements that might trigger precise future results to vary materially from latest expectations encompass the following: quick technological exchange; Datawatch`s dependence on the introduction of latest products and product enhancements and viable delays in those introductions; acceptance of recent products by using the market, competitors within the utility industry commonly, and within the markets for next generation analytics in particular; and Datawatch`s dependence on its major products, proprietary application technology and utility licensed from third parties. further assistance on elements that could cause exact results to differ from those predicted is exact in various publicly-available files, which consist of, however are not limited to, filings made via Datawatch every so often with the Securities and change commission, together with however now not constrained to, those appearing within the business`s Annual record on kind 10-okay for the 12 months ended September 30, 2015. Any ahead-searching statements may still be regarded in gentle of those factors.
© 2016 Datawatch company. Datawatch and the Datawatch brand are emblems or registered emblems of Datawatch organization in the u.s. and/or different countries. All other names are trademarks or registered emblems of their respective companies.
Media Contact:Amanda BeaupreMarketing Communications manager, Datawatch Corporationamanda_beaupre@datawatch.com 978-275-8387Twitter: @datawatch
This announcement is allotted by NASDAQ OMX company options on behalf of NASDAQ OMX company options shoppers.
The provider of this announcement warrants that they are solely accountable for the content, accuracy and originality of the counsel contained therein.supply: Datawatch service provider via GlobeNewswireHUG#2011258
final November, we puzzled what IBM expects to return out of its acquisition of Canadian business intelligence software provider Cognos. This morning we discovered, as massive Blue enters the "company optimization" company.
new york metropolis (BetaNews) -- At a press convention right here today, the lately combined IBM/Cognos firm put forth a sparkling challenge to business utility rivals SAP and Oracle, unveiling neatly over a dozen new products.
officially dubbed "company optimization" through IBM, the market being addressed represents a big and transforming into possibility, observed Steve Mills, senior vice chairman and neighborhood executive for the IBM utility neighborhood.
"there's absolute confidence (now we have been) looking to benefit share towards SAP and Oracle," Mills told reporters nowadays.
however with the acquisition of Cognos finished, IBM is already forward in the business optimization market, in keeping with the senior VP.
"the mixing between Cognos and IBM places us capable that different corporations are going to be chasing," he said.
IBM plans to fulfill the needs of corporations of all sizes through an "tips on Demand" (IoD) architecture a good way to latitude from core database management and content material administration techniques on the backside layer to client choice-making tools on the properly layer.
Six of the new options IBM introduced nowadays supply purchasers pre-integration between the Cognos company intelligence (BI) gadget and quite a lot of existing products from IBM, for applications involving wider use and more advantageous analysis of company advice drawn from a number of sources.
different new products consist of really good vertical solutions for markets that consist of banking, retail, fitness care, and lifestyles sciences.
IBM's new Retail save Operations, as an instance, permits retail managers to order new supplies whereas on the same time projecting stock degrees of existing substances a couple of weeks ahead, noted Marc Andrews, IBM's director for IoD and Cognos advertising Integration, in a gathering with BetaNews at the press event.
IBM additionally announced a collection of IoD Infrastructure functions, to be offered to customers via each the enterprise and technical palms of IBM global Consulting.
IT managers from pizza chain Papa Gino's and backyard tools company Fiskars manufacturers, additionally available at the event, described how they're the use of the integrated products to rapidly compile aspect-of-sale (POS) information from retail outlets right through the USA and distribute the tips to business managers for enterprise analysis.
Over the next couple of years, IBM will announce significantly more products in the "tips on Demand" category, Mills referred to.
as an instance, Cognos' BI equipment are expected to take on a great deal more subtle analysis capabilities, developed at IBM's research labs.
other than Retail keep Operations, other vertical options rolled out by way of IBM these days protected Crime administration and perception; Municipal performance administration Scorecard; BI for health Analytics; existence Sciences Promotional Spend and Compliance; monetary Planning; financial chance insight in Banking; possibility Adjusted Profitability for Banking; group of workers Analytics; and Manufacturing income and Operations Planning (S&OP) trade answer.
IBM also rolled out a really expert repository and content administration device favourite as the IBM Compliance Warehouse for prison manage.
For more: IBM contrasts its 'integration' with Cognos towards SAP's 'acquisitions'
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IBM Cognos Financial Statement Reporting Developer
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No result found, try new keyword!... disclosure management and report as well as equity compensation tools. Acquired products: IBM Cognos Disclosure Management, Cognos Disclosure Management on Cloud, Cognos Financial Statement Report...
Instead of just focusing on the major features of IBM Cognos 10 Report Studio, Roger Johnson, coauthor of IBM Cognos 10 Report Studio: Practical Examples, looks at some lesser-known tools and object properties to further enhance your Report Studio projects.
From the author of
The biggest additions to IBM Cognos Report Studio in version 10 have been Active Reports and Statistics objects. These two new ways of presenting data provide many new options for report authors to create reports that match the analytical needs of the user community. Entire classes have been created to focus on the creation of reports using these formats.
Other capabilities in IBM Cognos 10 Report Studio include the integration of external data sources and the ability to save Report Studio reports to be used directly by Business Insight Advanced authors. Using external data sources in Report Studio has been a customer request since IBM Cognos tools moved to a web-based architecture. This enhancement gives the report consumer new opportunities to process just the information needed for a specific situation. By using a common report definition between applications, users who aren't accustomed to complex reports can receive assistance to build reports that have features beyond those normally available to Business Insight Advanced users.
While the features I've discussed to this point are promoted as key features, other useful options in version 10 will increase the effectiveness of reports to your users. Some of these features were previously available through complex programming by the report developer, but IBM Cognos Business Intelligence now makes this job much easier. As a report writer and instructor who can appreciate the ability to create report designs designed to tell a story, I want to highlight 10 of these new features.
The Alternative Text property has been added to graphical objects, such as images and charts, to allow screen readers to translate the text (see Figure 1). Another aspect of this feature that's applied in various properties is to provide localized text without using conditional formatting.
Colored Regions, Plot Area Fill, Material Effects
The Colored Regions, Plot Area Fill, and Material Effects properties allow charts to have more creative designs in order to enhance the overall presentation of the charts. Mixed with other chart presentation options, these features help report developers to give new polish to the presentation of content. Figure 2 shows the additional gradient options that are now available, along with the new properties for the charts.
New Gradient Fill Types
Moving beyond simple linear gradients, some new fill types provide more choices for enhanced presentations. Backgrounds behind pages, objects, and selected areas can now display a number of gradient designs. The fill types include rectangular frames and embedded circular gradients, with many parameters to customize the blending of colors (see Figure 3).
Chart Combinations (Primary Axis, Secondary Axis, Primary Bottom, Secondary Bottom)
IBM Cognos 8 Business Insight had the ability to set Y1 and Y2 axes. Now combination charts can be stacked with two more axes for better analysis of related numbers. These options can be integrated into dashboard design to enhance the presentation of related measures. Figure 4 shows a chart with the additional axes selected.
Query Calculations in Query Explorer Replace Calculated Member, Calculated Measure, Set Expression, and Intersection (tuple)
In IBM Cognos 8 Report Studio, different objects were created for each of the dimensional functions. Now they're all bundled into the Query Calculations (see Figure 5). This option simplifies the toolbox for report authors, while emphasizing that dimensional queries can have enhanced calculations.
Summarize Small Slices and Exploded Slices
With pie charts, two improvements include summarizing small slices and exploding slices. These two options greatly improve the presentation of pie charts to emphasize the most important information (see Figure 6). In my classes, these options have been requested for years, and now they're delivered in this release.
Trendlines, Category Baselines, and Numeric Baselines
Report Studio functions have now improved on the predictive ability behind charts, without having to use external functions to calculate the numbers (see Figure 7).
Series Color Synchronization
With the changes made to enhance series, this feature allows report writers to simplify the legends when the series information is repeated across the combinations. By changing the Series Color property to Match (see the short arrow in Figure 8), the legend shows the different product lines and the nested measures differently (indicated by the longer arrow), increasing the effectiveness of the presentation.
Custom Properties for Prompts
Dimensional Set Definitions
As a welcome addition to dimensional functions, the Set Definition option (see Figure 10) allows report authors to create complex subsets that are presented graphically. This feature can make troubleshooting complex sets much easier by providing a more modular approach to set development. This was the best new property for me, since it simplifies the development of sets that had to be full of nested functions.
Posted April 18, 2013 By Drew Robb Feedback
While Big Data can be useful in fighting fraud, traditional business intelligence tools aren't much help.
If it was easy to detect fraud, there wouldn’t be much of it around. But these days, the sheer volume of information being generated makes it more difficult than ever to detect.
“Organizations today typically have a fragmented approach to dealing with security and fraud risks, which leaves them vulnerable to even more attacks as criminals are quick to find and exploit any points of weakness,” said Ellen Joyner-Roberson, global marketing principal at SAS Security Intelligence Solutions. “As a result, security risks and financial crimes are increasing dramatically due to a weak global economy, growth in organized crime and the increasing sophistication of fraudulent schemes.”
Not Your Usual Analytics
Unfortunately, many current analytics systems do not support robust analytical modeling, making it difficult to process and analyze information fast enough to make a difference. Different departments often have disparate data sources and processes, so it’s tough to spot suspicious activity across the enterprise.
In addition, there is a constant struggle to balance tougher anti-fraud efforts with a good customer experience. If vendors stop more transactions that are suspicious in an attempt to reduce fraud losses, they may anger customers trying to complete legitimate transactions.
Banking, insurance, government, health care and retail are obvious targets for con artists. The banking industry, for example, has a big problem with identity theft and account takeover. There, it is critical that decisions are made in real time at the point of sale, which requires a monitoring and analytics approach that can instantly model for behavior changes and stop that transaction without getting it wrong too many times.
Due to such demands, the consensus is that traditional business intelligence (BI) isn’t sophisticated enough. It needs to be backed up by domain-embedded rules and adaptive analytics that can be tailored to different types of fraud or financial crime. Context also plays a vital part, and integrating contextual information from mobile apps and other channels can heighten success. And geospatial and velocity data capture at transaction origination should be backed up by decision making in real time.
“To fight fraud before it causes financial losses, companies are using real-time interdiction (definition: to forbid or debar) capabilities wherever they can, and with raw response times under 200 milliseconds,” said Joyner-Roberson.
Her company developed SAS Security Intelligence to address this market. It comprises various SAS products to address fraud and improper payments, regulatory compliance and security. This includes SAS Fraud Management, SAS Network Analytics, SAS Financial Crimes Suite and SAS Fraud Framework.
SAS Security Intelligence takes an enterprise approach to data management and consolidation, combining data integration, data quality and master data management into a unified environment that brings together cross-channel enterprise data on a single platform. It has the ability to score and decision all transactions in real-time and intercept suspect deals.
Haystacks, Needles and Big Data
Big Data only magnifies the problems inherent in tracking down wrongdoers. Just how do you deal with capturing, processing, and storing massive amounts of real-time data so you can learn and adapt to changing behavior patterns?
“The needle in the haystack analogy is particularly appropriate for fraud detection due to the small amount of fraud compared to the whole of legitimate Web traffic,” said Jesse McKenna, head of Threat Research for Silver Tail Systems, RSA. “However, as fraud patterns constantly shift and evolve, so does the needle you are looking for. Today it may be a needle, tomorrow a pushpin or a nail.”
The challenge is that you don’t know exactly what you are looking for other than it will be different than the rest of the pile. While Big Data means you may be able to derive more insights, finding the meaningful data and building detection algorithms that aren't brittle and won't quickly become irrelevant takes a deep understanding of fraud.
That’s where behavioral analytics and adaptive detection methods become important. You need ways to isolate what is different that you may have never seen before.
Analytics apps also have to be of value to fraud investigators, who are the ones with the experience of the real world. Machines can burn through the data mountain to locate unusual occurrences, but they are nowhere near as good as people at evaluating and understanding context. Therefore, the app has to facilitate the people or fraud units it serves, not burden them with delays or lengthy procedures.
RSA’s Silver Tail Systems product suite (consisting of Forensics, Mitigator, and Profile Analyzer tools) provides behavioral analytics, real-time custom rules and mitigation capabilities, as well as a forensics interface for performing investigations.
For example, by monitoring the details of every HTTP/S request that is sent to a website, it learns what normal behavior looks like for the website and can then identify criminal behavior and alert the appropriate teams for investigation. Alternately, it can communicate with other network devices to redirect or terminate the Web session in real-time.
User-based behavioral analytics (in addition to the population-based ones) helps identify when a particular user is deviating from their normal behavior, as is the case with many fraud and account compromise scenarios.
“Silver Tail was created by ex-eBay and PayPal fraud professionals who lived the battle against fraud at a time when they were protecting the two most targeted brands on the Internet,” said McKenna. “Their experiences motivated them to keep up with shifting Web fraud attacks instead of playing catch-up.”
IBM is also involved in fraud analytics via a combination of IBM SPSS Modeler, SPSS Statistics, SPSS Collaboration and Deployment Services, SPSS Data Collection, SPSS Decision Management, IBM Cognos BI, Cognos Express, Cognos Insight, Cognos Disclosure Management and Cognos Financial Statement Reporting.
IBM believes that visualization is a vital part in making sense of analytics information, especially when it comes to facilitating the work of professionals in fraud detection.
“As data volumes continue to go up, BI tasks can benefit greatly from the use of information visualization techniques,” said Don Campbell, CTO, IBM Business Analytics. “Good visual representations can help individuals intuitively understand complex data. Visualization can be a powerful presentation and information consumption interface. But it doesn't stand on its own.”
Graphical representation is also a focus of 21CT, a provider of analytics for investigation and pattern detection. It has released enhanced graph search for its LYNXeon product to help spot cyber attackers and document criminal behavior. The rationale behind the product is that machine -based attacks can be caught by machines, but human-based attacks require specialized tools to help people detect them before the damage is done.
“Health care fraud, notably Medicare, is an enormous problem, costing billions a year,” said Kyle Flaherty, vice president of Marketing at 21CT. “The challenge is not only the enormous amounts of data, but also in the disparate connections within the data. Additionally, fraud has been rampant in this arena and the malicious entities have become sophisticated.”
While regular BI tools provide insight into one slice of the overall information, Flaherty said, they are not good enough for fraud detection, which depends on operational insight and the ability for a human to hunt through visualized data, discover links, and detect overall patterns of activity.
“Fraud detection is a human versus human battle, and BI tools can spit out more data and graphs to help illustrate the problem,” said Flaherty. “In the end you need to be able to hop around the data and investigate.”
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in California, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).
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