Business Intelligence (BI) Tools Forum
Jul 07 2020
What types of insights do businesses gain from BAM as opposed to BI?
reviewer1208820BAM is a great way to look at daily production of your business in real time, using solutions such as DMI (direct machine interface). BI is taking all of the data that you have accumulated and using that data to lead your business into the future with help of tools such as Microsoft BI, Minitab, Microstrategy and so on.
David PiechBusiness Application Monitoring usually involves measurement and monitoring of up time of key systems, whether that be ERP, CRM, HR, etc. System uptime, downtime and performance response time are some of metrics usually associated with BAM. BI analytics are much more granular and business specific such as gross profit, inventory costs, AR days outstanding and are accessed via dashboards and reports.
Jorge BarrosoThe difference between BAM and BI mainly recides in the way that the information is use, for example in many cases the information collected for BI is historical to the bussiness and for support to set goals in short, médium and logn term could be use to establish the estrategic decition most convenient. On other hand BAM, mainly use the information on a day to day basis about the results of bussiness processes and to act proactively to reach the operational bussiness goals of the processes with the information that could be part of the dashboard.
May 16 2020
Hello Experts, I am working as a Solution Architect at a global enterprise tech vendor. I have 2 RPD files, a.rpd and b.rpd. I need to switch between these 2 RPDs on the same server and through the same OBIEE tool. Do I need to deploy both RPD files on the server to switch between these two through the same OBIEE tool? As per my own attempt, I can open both RPD files through Administration (obiee tool) : File --> Open-->Offline and without any deployment. Is it mandatory to deploy both RPD at server to open it online? I guess I need to define 2 different ODBC system data sources for my repositories after deployment. Thanks.
Feb 24 2020
Which BI tools are the best out of the box for basic calculations that all SaaS businesses need to track to survive? Are some tools better for startups vs enterprise?
MahalingamShanmugamLooker, Domo, Sisense, Tableau, and Power BI are tools are good for enterprise. If you are looking for SMB (Small Medium Business), where you have 5-10 users who use BI for portfolio, then you should look at small Startup (ConverSight.ai, ToughtSpot etc.) for a per-user license, which is comparatively low in the market.
ChunqiangGongI think Qlik is strong at data processing and has a high performance within a large scale of data with its unique in-memory database.
Patrick MyreholtTIBCO Jaspersoft
Feb 21 2020
When evaluating Business Intelligence Tools, what aspect do you think is the most important to look for?
Let the community know what you think. Share your opinions now!
it_user354258Total cost of ownership is often overlooked during BI product selection. Cheap products do not equal cheap ownership experiences, whether it is missing functionality which must be provided by additional products, poor integration of modules which causes duplication of effort, weak support from the vendor, high cost of maintenance or constant changes to the product portfolio. The key factors to consider are: Is this product right for the intended user-base? It should not be necessary to purchase one product for IT, one for business analysts and one for 'end-users'. There are considerable cost savings associated with using a single platform (not a single vendor with many products they have built or bought). Does the product have the depth of functionality needed, and foreseeably anticipated? Is that functionality accessible? Can an expert easily access complex, deep functionality, without the occasional or new user being overwhelmed by the interface? Can it reach all the necessary data sources? Both inside and outside the corporation. How fast is the user experience, both in developing reports and dashboards and in retrieving the data? Speed of both allows iterative learning and development by new and occasional users, while ensuring high productivity for expert users. Does it work with our real world data? Too often evaluation of products still relies on superficial test on restricted volumes of data, or the lower complexity data as "it would take too long to build a fully representative testing environment" - big mistake. Identify the product(s) you believe are suitable and then bear the cost of proving they can deliver in your own use case. Too often a poor acquisition is followed by increasing spend to "make it work", when money spent earlier on selecting and proving the right tool would lead to much lower overall cost of ownership and more importantly early success and hence ROI. Does the company have a history of good backward compatibility? You will build a vast amount of intellectual property with a BI tool. You will become dependent on the insight it provides your organization. So investigate how well you chosen product has allowed users to migrate that IP forward through new revisions of their products. Rewriting IP is a good opportunity to clean it up and start over, but it's a massive unnecessary expense if you have built what you need and it is the vendor forcing you to rewrite your work.
it_user17526I believe you have to match product capabilities to company BI strategy first and then consider infrastructure standards and internal competencies. if you do these things you should get value. The type of BI solution is important but don't be fooled by the "it's all about data visualization or big data". it is not in most organizations...
it_user124860Most folks tend to think of UI and the flashy, sexy stuff. However, experience has proven that adopting a platform approach is key to success - a Platform that can access any data source and provide capabilities for internal and external users from the same platform, and not merely serve as a data visualization tool. The ability to do disconnected analytics cannot be discounted; Further having a platform that does NOT mandate creating a data warehouse as a prerequisite; i.e. It shoild have the ability to access operational data sources with minimal impact to the back-end systems.
Feb 13 2020
One of the most popular comparisons on IT Central Station is SAS Visual Analytics vs Tableau Which of these two solutions would you recommend and why? Thanks! --Rhea
it_user653898Selection of a tool depends on your tech environment and the intended use of the tool. If you have a strong staff with a data mart, data warehouse or data lake in place then a number of tools would work. Tableau is the 500 lb gorilla, but it isn't as nimble as Qlik, Yellow Fin, Looker or Sisense. If you don't have a large team and want an automated data mart then look at Birst. It isn't as "beautiful" as others, but does a good job of delivering what the customer requires with less work on the back end. Good luck!
it_user802398I have more experience with SAS VA not with Tableau. Weak points and strengths Tableau - Probably one of the best visualization analytic tools for final users - Cloud or on Premise - Quickly to deploy - Some specific functions to predictive analytics out of the box (linear regression, etc.) - Connectors to Big Data, etc. SAS Visual Analytics - See new features with Cloud SAS Viya (new architecture and integration with other SAS Solutions) - Powerful vision of analytics and statistics with SAS Visual Statistics in the same framework - You don’t need a Data Scientist people to develop predictive or advanced analytics models - Deploy a powerful analytics model in few moments - It supports a Big Data and a lot of connectors. Some payments - No needs code as easy to use - You can use and specific and free App for mobile users - Price: Pay for cores, not users. Weak points It needs a lot of machine resources (RAM and CPU) Very complex to install. You need specific SAS partner support Poor graphics vs Tableau or Qlik Sense Normally you need the Enterprise Guide or other ETL solution to data prepare
it_user97749From my perspective, SAS is very rich but its origin lies in the programming. Therefore, knowledge in setting up programming use and direction is somewhat implied. Targeted to a more technical data science audience. Tableau, on the other hand, is focused on a visual end-user perspective. Therefore, the target is a business analyst who focuses on what the data implies - somewhat agnostic to the statistical techniques focus.
Feb 06 2020
I am researching BI tools in the Oracle world. Which would you recommend and why? Thanks! I appreciate the help. Pierre-Paul
Russell RothsteinThere's OBIEE, have you ruled that out? Seems like it is not highly rated based on reviews: https://www.itcentralstation.com/products/oracle-obiee-reviews Here's a review of someone using DOMO in an Oracle environment: https://www.itcentralstation.com/product_reviews/domo-review-62133-by-kim-galan This reviewer compared Oracle BI with Tableau but chose Tableau: https://www.itcentralstation.com/product_reviews/tableau-review-63022-by-cristobal-rodriguez
Ram ChittaPower BI..Cost Effective, Self Service BI, Highly Graphical, Cloud Ready, Operational Report, Data connectivity.
Goran CekolI would definitely recommend IBM Cognos. I have worked with many BI solutions that were based on IBM Cognos and Oracle. If budget is an issue then PowerBI is a very good solution too. I have also worked with some open source big data solutions - for reporting and visualizations Apache Superset and for OLAP Apache Kylin.