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COG-632 exam Dumps Source : IBM Cognos 10 BI Metadata Model Developer
Test Code : COG-632
Test appellation : IBM Cognos 10 BI Metadata Model Developer
Vendor appellation : IBM
: 53 true Questions
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IBM IBM Cognos 10 BI
As they settle for and welcome the entrepreneurial culture with open hands, it gives guidelines to agencies about the feasible hazards of going out of company if they don't occupy the faultfinding precautions to live on the competitors. This includes adopting alternate and opening your repartee to recent technology that can improvement the enterprise and uphold it stay competitive within the long-time period. IBM strives to present individuals and companies know-how that contributes to their progress.
ExistBI brings you licensed IBM InfoSphere DataStage practising and IBM Cognos training from licensed, skilled, and award-successful people to emphasise the significance of IT in working a enterprise. They accept as dependable with in using technology to empower every enterprise to dwell within the race and not live left at the back of.
Why You want IBM Infosphere Datastage working towards
With a robust ETL (Extract, transform, and cargo) manner, a company can dig profound into massive records units via queries and retrieve significant counsel that can live a excellent concept for the company. furthermore, with effectual integration, that you can steer clear of any delays in decision-making, which may uphold you gain first-mover talents in an already saturated market. With InfoSphere DataStage, IBM brings you a sophisticated ETL device in order to no longer best uphold you construct information, however additionally signify you can present it graphically and occupy selections in dependable time, saving you from a misplaced chance.
ExistBI’s working towards software covers every thing, from administration to architecture and programming to information processing to assist you to accumulate a complete concept of the utility. moreover, their partnership with IBM permits us to convey licensed getting to know fabric and fingers-on working towards from certified individuals every bit of throughout the globe. With DataStage, they are able to uphold you view at a strategic growth.
How IBM Cognos is distinctive
in contrast to InfoSphere DataStage, IBM Cognos is a business intelligence utensil that is web-based. It presents entertaining rig for analytics, reporting, metrics, score carding, and monitoring. The a few add-ons of IBM Cognos that encompass a framework manager, cube dressmaker, and transformer permit for the efficient processing of facts and formulation of relationships to achieve at actionable effects. The Cognos express addition additionally allows company users to plot, budget, and forecast, which is constructive in production, earnings, advertising, analysis and development, and other departments.
With a enterprise intelligence device love Cognos by passage of your facet, you could arrive at advantageous and principal information that is enjoyable and catered to your particular wants. The sources could live previous business information or records picked up from numerous sources within the users’ neighborhood to aid you maintain in repartee the market traits and what can live anticipated in the future. and not using a BI tool, surviving this changed era may well live a problem. With ExistBI’s IBM Cognos practising, you maintain got more suitable probabilities of stumbling upon whatever thing entertaining in an application to interest the hundreds than devoid of it.
Why elect ExistBI
Our commitment to empowering businesses with know-how is only a step against achieving every thing the region has to offer. organizations exigency BI application and rig to gain more informed choices and emerge because the winners. With their IBM practicing features and solutions, they train to aid groups regulate to the concurrent world.
To learn more about us, consult with their YouTube channel, “ExistBI — Uniting enterprise and technology.” To birth off with, click on on this link and lope through their videos on enterprise intelligence: https://www.youtube.com/playlist?list=PLREDZv-uBI06RtZQVGpI15_ETc3ExlJab.
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IBM’s cloud computing strategy is manifest to some extent with Cognos 10, the latest unencumber of the business intelligence platform.
As a Part of Cognos 10, IBM is delivering a cloud-based provider they appellation Cognos 10 within the Cloud.
It’s a hosted provider for companies that wish to transfer its license to the cloud or fully host online.
The strategy offers some perception into the IBM utility group’s method to cloud computing.
We note three distinctions to the Cognos approach and how it reflects on IBM’s approach.
Hosted, now not SaaS
The carrier has the identical aspects that comes with Cognos 10, arguably the highlight of IBM’s tips on exact convention. It aspects predictive analytics and social collaboration capabilities through its integration with Lotus Connections.
Cognos 10 in the Cloud is not in the vein of a traditonal SaaS provider. You pay a license fee for internet hosting your license. shoppers might likewise switch the license from on-premise to the IBM Cloud. valued clientele might likewise also elect to purchase a hosted license without investing within the on-premise carrier.
Streaming information from the Cloud
Cognos 10 is a cumbersome obligation analytics engine. SPSS is baked in. It pulls in information from the cloud, including unstructured statistics. users can employ third-celebration information to accumulate a historical evaluation, note a true-time circulation or enact “what if,” analysis.
less About Cloud, greater About beginning
It’s questionable if there's exact for a absolute cloud computing service. companies maintain profound investments in information centers but they are searching for the birthright passage to prolong to a cloud environment. That’s a trend they note a distinguished deal from SAP, VMware, Microsoft and a host of others.
IBM says it’s approach with Cognos 10 is much less about the cloud than start. valued clientele crave a situation to position their application license. That’s the genesis IBM is making with Cognos 10 within the Cloud.
we maintain questions concerning the IBM method. it’s just a minute Part of IBM’s cloud providing but it’s illustrative of a larger strategy to gain employ of the cloud as an option birth model for usual application offerings.
Posted October 26, 2010 via Paul Shread feedback
IBM provides collaboration, cellular uphold and straightforward-to-use analytics to its flagship BI application.
At its recent company Analytics discussion board in Las Vegas this week, IBM (NYSE: IBM) persisted its aggressive push into enterprise intelligence and analytics with a number of recent product releases, including the newest release of its flagship BI application, Cognos 10.
additionally at the recent convention for Cognos and SPSS users, big Blue unveiled DB2 10 database utility with a forty percent performance boost, IBM InfoSphere Server eight.5 statistics integration and pleasant software, and a expertise preview of Hadoop-primarily based big data analytics application.
Cognos 10 boasts a few recent facets, together with collaboration and analytics capabilities and iPad, iPhone and BlackBerry help.
IBM expenses Cognos 10 as "probably the most vast analytics offering because the acquisition of Cognos" three years in the past. The addition of Lotus Connections software adds social collaboration and the capability to talk as considerations arise.
IBM likewise claims "intuitive navigation capabilities and simplified user event" that "eliminates the frustration of having to interrupt user instruct of notion on account of the exigency to swap between views to accumulate the birthright tips."
The application offers an built-in view of ragged assistance with precise-time updates. users can select various views from essential true-time suggestions to advanced predictive analytics.
IBM said Cognos 10 "takes analytics out of the typical structure of reports and charts to a more interactive design and broader evaluation and perception, making it less demanding by using proposing built-in photographs and movies to usher business clients. they could now profit instant perception with analytics in an effortless to employ layout every time, anywhere on their mobile gadgets."
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Data Warehouse Concepts
What is a Data Warehouse?
A warehouse in general terms is a repository where they store their information. Coming to the data warehouse, it is a collection of data organized in a specific manner and categorized information.
A data warehouse stores historical data of an organization so that they can resolve their performance over the past years and scheme for the future.
The favorite definition of the data warehouse by WH Inmon:
A data warehouse is:
Subject oriented: Data in the warehouse is categorized in different subject areas. For example, deem a KFC store. It has many branches every bit of over the world. If they maintain to resolve “sales” for India, this is termed as “subject”.
Integrated: A data warehouse has data coming from multiple sources which are integrated into the warehouse. For example, deem the very KFC store, stores in India may store date bailiwick as “dd/mm/yyyy” whereas the very data in another country will live stored as “MM/DD/YYYY”. The data warehouse will maintain only one format fixed to boom “MM/DD/YYYY”.
Time-Variant: A data warehouse stores historical data with which they can identify patterns of sales over a time age of 3 months,6 months or 2 years of any organization which has a warehouse.
Non-Volatile: Data in the warehouse will not change once it is entered.
Another definition from Ralph Kimball is more precise:
A data warehouse is a copy of transaction data specifically structured for query and analysis.
What is a Data mart?
A data mart is a subset of a data warehouse. Suppose they maintain an organization established in many different locations and each location maintains a data warehouse which they summon it as data mart because a warehouse will maintain every bit of the data integrated and as far as data mart is considered it will live a Part of the data warehouse.
What are uses of having a Data Warehouse?
A Data Warehouse, in general, is used to resolve trends over a age of time and enhances the determination making of an organization. Once the data is loaded into the warehouse will live creating an OLAP cube or directly employ the data to resolve trends. Basing on which the top level management will approach their future business strategies.
Data warehouse Architecture
We will multiple sources there every bit of the operational data will live stored. Some may store them in flat files and some in databases. They will maintain to read every bit of the sources and accomplish ETL (Extract, Transform and Load operations) which will live used to integrate data from these sources and transform them into one unique structure and then load into their target data warehouse.
Data Warehouse Architecture
There are 2 approaches in designing your data warehouse. First one is “Top-Down approach” and second is “Bottom-up approach”.
Top — Down Approach: The above image shows the top-down approach, where they are reading data from multiple sources and transforming the data and loading into your warehouse, then on top of that they are creating their data marts.
Bottom-up Approach: The antithetical of the above approach is this. Here they will live creating data marts first and then they will create their data ware house on top of every bit of the data marts.
Data Warehouse Terms
Dimension: A Dimension is a categorical information which is stored in a data warehouse.
Fact: Fact is a measurable quantity by which they can actually figure out what the dimension does.
Attribute: Attributes are the elements in a dimension Ex: Suppose they maintain product information classified in a dimension. The attributes of the “Product dimension” are: “Product_ID, Product_Name, Product_Color” etc. Sales is a fact table where you store numeric values associated with the dimension attributes.For instance, they maintain to cipher the number of sales of each product for the current month.In this case, Product is the dimension and Month is a dimension and numbers of product sold is the fact.
OLAP: Online Analytical Processing is a multidimensional model using which users can view data in multiple dimensions at a solitary glance.
Types of OLAP’s:
OLTP: Online transactional processing is a transaction based model where the main train will live to retrieve data faster and update transactions quickly.
Schemas in Datawarehouse
The schema is a rational arrangement of tables in a data warehouse. They maintain schemas in relational databases. Very much love very Data warehouse has schema’s namely Star schema, Snowflake schema, and Fact-Constellation.
In this rational arrangement of tables, the fact table will live at the center of the schema surrounded by multiple dimension tables. Fact and dimension tables are linked via a Primary — Foreign Key relationship. Fact table will live having alien keys of every bit of the Dimension tables along with the facts whereas a Dimension table will live having attributes which recite the Dimension.
In this rational arrangement of tables, they maintain dimension tables connected to other dimension tables which in turn are connected to fact table via a primary-foreign key relationship. Else they can boom that the Dimension tables in Snowflake schema are normalized. Because of the normalization, the data redundancy will live reduced and a lot of storage space is saved.
Fact Constellation Schema:
A fact constellation schema, unlike the start or snowflake, will maintain multiple fact tables. It is likewise called as Galaxy Schema.
Star Schema Example
In this schema shown, a fact table (sales) is connected to multiple dimension tables item, location, time and branch. Each dimension table has attributes describing the dimension and fact table has the alien key of every bit of dimension tables along with facts love dollars_sold and units sold.
Snowflake Schema Example:
In this schema, a fact table (sales) is connected to multiple dimensions, whereas the dimensions item and location are again connected to City and Supplier dimension respectively.
Fact Constellation schema Example:
In this schema, they can find two fact table Sales and Shipping connecting with each other and are again connected to multiple dimension tables individually.
Now they are jumping into the actual topic “Cognos business Intelligence”.
Overall DWH architecture
We will live dealing with Cognos reporting utensil and Cognos Metadata managing utensil and other useful tools that Cognos BI has.
Let’s Go through where BI will actually arrive into picture
The below image shows overall Data warehouse Architecture. From data load to using the data loaded into the tables for enhancing the business of your organization. From every bit of the data sources (may it live Operational databases, Flat files etc.) they load the data into data warehouse through different ETL process and creating cubes and using the data for mining purpose.
The below figure will recite the business Intelligence rush how the data will live used for business optimization. business intelligence is a process from where you will live able to derive methods to enhance your business with the data that you have. Using BI one will live able to view at their data at different levels and will live able to gain decisions to gain their business better.
Cognos BI will live used to generate reports (list, crosstab, and charts). The below figure will exhibit you the entire rush that happens with Cognos.
The first step in using Cognos BI is to amass requirements. This is viable when you understand your business structure and the data that drives your business. Once the requirement is finalized the next step is to create your framework metadata model. You can elect either to you star schema or snowflake schema or you can employ the existing relational model.
After this step is done with they maintain to publish the model that they maintain created. Publishing the model will gain your metadata model available for reporting purpose. Once your model is published, they can employ the model to create different types of reports as per your requirement and they will schedule the reports basing your requirement.
Different Versions of Cognos
Cognos ReportNet (CRN) is a web-based software product for creating and managing ad-hoc and custom-made reports. ReportNet is developed by the Ottawa-based company Cognos (formerly Cognos Incorporated), an IBM company. The web-based reporting utensil was launched in September 2003. Since IBM’s acquisition of Cognos, ReportNet has been renamed IBM Cognos ReportNet love every bit of other Cognos products.
Cognos Report Studio — A Web-based product for creating involved professional looking reports
Cognos Query Studio — A Web-based product for creating ad-hoc reports.
Cognos Framework Manager — A metadata modeling utensil to create BI metadata for reporting and dashboard applications.
Cognos Connection — the Main portal used to access reports, schedule reports and accomplish administrator activities.
IBM Cognos 8 BI, initially launched in September 2005, combined the features of several previous products, including ReportNet, PowerPlay, Metrics Manager. There are likewise Express and Extended versions of Cognos 8 BI. replete features:
Report Studio (Professional report authoring utensil formatted for the web)
Query Studio (Ad hoc report authoring utensil with instant data preview)
Analysis Studio (Explore multi-dimensional cube data to respond business questions)
Metric Studio (Monitor, analyze, and report on KPIs)
Metric Designer (Define, load, and maintain metrics to live available in Metric Studio)
Event Studio (Action based agents to notify determination makers as events happen)
Framework Manager (Semantic metadata layer utensil which creates models or packages)
PowerPlay Studio (formerly PowerPlay Web)
Analytic Applications (Packaged BI Applications, built on an adaptable platform and extensible into business Analytics)
We can note different components and how they are fitting in. The top most layer, where they can note Cognos Connection, Administrator, business Insight and different studios. They every bit of are web-based and end-user needs not to install any client side software if he has the latest web browser installed.
The bottom layer is basically data layer where you may maintain homogeneous or heterogeneous database systems. Data may live relational or multi-dimensional. On top of it, they can note three modeling tools there — Framework Manager, Transformer, and Metric Designer. every bit of of them are client based installation.
We’ll maintain the rush of components from top to bottom as shown in below BI components figure.
Before getting into the actual topics about how you create the model, deploy it and employ it to create reports they maintain to first know the architecture of Cognos.
Cognos business Intelligence framework is 3- tier architecture. The first tier of the architecture will live having the Web server which is responsible for the accessing the user interfaces. The second tier will live having IBM Cognos BI Server which will live having gateways and dispatchers to route requests from different UI’s to Database and communicate back to the server.
The Third Tier will maintain the data sources. You can maintain multiple data sources and they will connect to the Cognos server using JDBC or API’s.
The Below figure shows the architecture of Cognos BI:
In the data tier, you can note one more component called the “Content Store” which is a repository for the Cognos server. Whenever you redeem any objects reports, models everything the data is stored in Content Store database which once you reopen or reuse the existing object created will fetch the data from the Content Store. every bit of this travail will live performed by the “Content Manager”.
Content Manager: The content manager is responsible for connecting with the Content Store database and saving any report or model back to the Content Store.
Dispatcher: The job of dispatchers is to route requests sent from and to the Web UI/Windows based components.
Web-based and Windows Based components of Cognos
Cognos BI has two types of components,
1. Web-Based components.
2. Window based components.
Web-based components includes
Cognos Connection: This is the portal from where you can access every bit of the web-based components of IBM Cognos BI.
Cognos Administration: Using this web-based UI you can accomplish administrative tasks love granting access, revoking access, creating users, groups and defining roles etc.,
Cognos Report Studio: Using Report studio utensil they can create reports and format the reports. They can create multiple types of reports love list report, crosstab reports, graph’s etc.,
Cognos Query Studio: Here they create ad-hoc reports. Ad-hoc reports are useful when a user wants to note the report without any prompts and less formatting. Using query studio they can create a report instantly.
Cognos Metric Studio: This studio is used to build customized scorecards reports to monitor and resolve metrics.
Cognos Analysis studio: This studio is used to resolve data from different dimensions and likewise compare trends.
Cognos business Insight: This utensil is used to build dashboards. A dashboard allows a user to quickly view into the data and enhance the determination making.
Cognos business Insight Advanced: With this tool, they can build more powerful dashboards and as well as simple reports.
Cognos Framework Manager: Cognos framework manager is a utensil used to create metadata models which they can employ in Report studio or analysis studio.
Cognos Map Manager: Using this utensil they can create maps which will allow you to create a recent region by using the existing regions.
No result found, try recent keyword!IBM has incorporated smart discovery in both its Watson Analytics and Cognos Analytics offerings and it is the leader in ML enabled BI. On the exact side ... design and build its core Metadata model ...
I’d love to thank Patrick Callahan, Senior Director at AmberLeaf for his contributions to this article.
Based on the interest from my ultimate article on hosted analytics, I decided to continue the trend and talk about businessintelligence in a software as a service (SaaS) mode. Customer relationship management (CRM) applications flocked to SaaS models based on the success of salesforce.com. Traditional on-premise vendors love Siebel, SalesLogix, Microsoft, Oracle, Onyx and the relaxation followed suit by providing SaaS solutions. The lure of no administration, no hassle upgrades, low switching barriers and fastimplementation times attracted many customers into the recent model.
However, business intelligence, database marketing and data warehousing maintain typically lagged these types of trends. It reminds me of the shift to the offshore implementation and uphold model. Datawarehousing lagged this trend due to the closer relationship between users and their uphold staff, the numerous requests for minute enhancements that exigency to live performed quickly and the massiveamount of systems integration between legacy systems.
Trepidation with SaaS models for business intelligence (BI) appeared for the very reasoning. As business intelligence became the center of big data integration and data trait efforts, concernsover the scalability and sophistication of SaaS vendors in this regard raised cautionary flags. In fairness, CRM systems are not without their data integration challenges, and the SaaS vendors haverisen to the occasion with APIs and other connectivity tools.
Nevertheless, progress cannot live stopped. It is BI’s turn to flight to the cloud and the software industry is responding.
Data Warehouse Infrastructure
The first major technologies from BI SaaS models are coming from the infrastructure side. recent startups are aiming at the Teradata/Netezza marketplace as highly scalable, incredibly fast, query(and data loading) processors. Using proprietary databases (sometimes columnar, inverted index structures with unique compression algorithms, sometimes with proprietary hardware, sometimes not), SaaSvendors are raising the bar in expense per performance benchmarks. Though Netezza is probably silent the leader in the performance category, Netezzainstallations suffuse a big premium for the effort.
Vertica may live the leader in this category. With some formalized benchmarks against Oracle, some price/performance studies against Netezza, andover 60 clients, they maintain grabbed some early market share. They maintain opted for an open architecture by creating an ODBC interface to their database so you can continue using your favorite reportingapplication. business Objects and Cognos on the business intelligence side and Informatica on the ETL side maintain every bit of certified on the Vetrica engine. Some recent skills will live scholarly as the physicalmodel for a columnar architecture is slightly different than a typical relational model. Vertica provides a data administration application that lets modelers design the rational model and Verticaconverts and generates the physical model.
Birst differs from Vertica in the sense that it provides an automated solution with its own front discontinue to its database and a data loader. Basically,you load up your data, and Birst figures out the optimal data model given its technology. The metadata is captured and automatically generates the user interface for the reporting piece, with sometailoring capabilities available. With its dashboard, Birst’s SaaS offering provides a consistent and central location for reporting output, making it easily accessible to many consumers.
With similar aspects to Vertica’s and Birst’s solutions, PivotLink’s SaaS delivery model includes a columnar architecture for their data store for performance, integrating data from various sources, and an optimized front-end to generate and deliver reports and dashboards for on-demand needs. With the front-end capabilities, PivotLink likewise provides report subscription and alert capabilities. Originally started as SeaTab in 1998, PivotLink has a solid customer list and several recent awards; PivotLink offers a tough SaaS BI option.
Other niche players worth keeping tabs on in this space are Information Builders, Oco and excellent Data.
Depending on the organization, you might find the open architecture of Vertica or the turnkey aspects of Birst and PivotLink, or the plumb analytics of LucidEra more advantageous. Each promote jumpstart implementations and proffer attractive pricing options and each should live closely evaluated for your specific BI needs.The SaaS model and each of these solutions are not birthright for everyone – if they enact fit, they provide a nice advantage. deem the following when evaluating SaaS:Open architecture to utilize gauge BI (ETL, reporting, etc.) tools
Data load performance
Dashboard and reporting sophistication
In the end, each of these organizations sees their meet in your business intelligence architecture similarly:For smaller organizations who maintain not adopted business intelligence just yet, these applications can act as your enterprise data warehouse or a federation of data marts.
For larger organizations, these services can act as specialized data marts with superior performance for extraordinarily demanding users, huge volumes of users, or users with cumbersome exploratory requirements.
For every bit of organizations, offering solutions with shorter implementation timelines and less IT involvement.
Analytical applications in a SaaS model is the other kind of genre I maintain noticed in the marketplace. Since many CRM tools arrive in SaaS, their reporting applications likewise arrive in the sameformat. However, specialized analytical applications maintain surfaced for specific business processes.
Probably most notable is Omniture as a web analytics provider. Omniture is by far the market leader in web analytics (maybe except forWebTrends and/or NetRatings). They provide management reports, ad hoc query and lately a suite of applications to uphold test your website design. For instance, if you are thinking of changing your registration page, you can employ their suite to accomplish an A/B (or far more complicated multivariate) test and monitor the results.
Hitwise, Compete, and Coremetrics provide countrywide (and in some cases international) web analytics across organizations. You can employ these applications to competitively benchmarkyour website activity against your competitors. You can note if you maintain spikes at the very time as your competitors or if changes in your website stole page consumption.
To illustrate how valuable analytics is to on-demand applications, VerticalResponse has recently overhauled the analytical component oftheir core email application. VerticalResponse is one of the leaders in providing marketing technology for minute businesses. They now provide benchmarks and scorecards so their customers can evaluatethe effectiveness of their campaigns, offers, creative and overall approach. They can essentially rank their campaigns and strategies in order to expand response rates.
Maybe you can even deem Panorama’s deal with Google Apps and Salesforce.com a hosted analytical application. Panorama has recently embedded their query technology into Google Spreadsheetsto uphold gain Google Apps more Excel-like. base functionality is free and advanced functionality is only $29/year.
LucidEra is my final solution in this group, offering SaaS BI analytics for ERM and CRM needs, having available pre-built plumb solutions or more general employ of their enterprise solution. Diverging kindly of from the prior solutions, LucidEra provides connectors for data integration and targets the ease of setup and employ for their solutionto very specific CRM (salesfoce.com) and ERM (Oracle) focuses. love most of the others, LucidEra’s executive team has a tough pedigree in the business intelligence and CRM arenas, and their direction has strengthened their position in the market.
I contemplate the concept of pre-canned, hosted applications for marketing response, sales targeting, sales analysis or customer analytics may provide a huge value for organizations – especially ifthese applications maintain plug-ins to favorite CRM and marketing automation tools love Siebel, salesforce.com, RightNow and Unica.
Though there is silent hefty concern (for excellent reason) about the ease of enterprise integration, quick changes and flexibility with business intelligence SaaS solutions, this wave will continueto expand as more customers opt for the model. I contemplate that the infrastructure vendors will exigency to prove that time to market does decrease, that this is just not a total cost of ownership play andthat they can gain their information pervasive throughout the organization (possibly in near real-time) if exigency be. Regardless, the several recent acquisitions by the BI behemoths (IBM and Cognos,for one) maintain altered the BI industry landscape, and the SaaS solutions mentioned in this article already maintain several competitive advantages that will gain it difficult for the larger organizationsto entrap up in the short term.
The issue with the application vendors is the long-term aspect of integrating their application with the relaxation of the organization’s data. For instance, for user level behavior, many clients wind up extracting particular data from Omniture into their corporate BI systems. Is that application worthwhile or should they bring web analytics completely in house? Point applications on a hosted levelwill exigency to maintain effortless ways of integrating data with the enterprise so they don’t become just another island of analytics.
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