Likelihood to Recommend Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
Read full review The proper management of SAP BusinessObjects Dashboards requires an expert on the team to manage and build reports. If an organization does not have the proper expertise on board to build and deploy reports it will fail. Data analytics, dropping into excel, and broadcasting of information are major bonuses for the use of SAP BusinessObjects Dashboards.
Read full review Pros Apache Spark makes processing very large data sets possible. It handles these data sets in a fairly quick manner. Apache Spark does a fairly good job implementing machine learning models for larger data sets. Apache Spark seems to be a rapidly advancing software, with the new features making the software ever more straight-forward to use. Read full review This software is easy to initially learn, and very powerful in producing reusable reports. It is much faster than my company's internal manual queries. The ability to build off of a saved query and share queries to other users is a great positive. My favorite part is that you can run queries in the background and it does not interfere with your current work or slow your computer down. Read full review Cons Memory management. Very weak on that. PySpark not as robust as scala with spark. spark master HA is needed. Not as HA as it should be. Locality should not be a necessity, but does help improvement. But would prefer no locality Read full review The installation can be very complex and time-consuming, it requires a lot of planning and foresight as to what role the software will play in the organization. The software has a relatively large learning curve that takes dedicated users months to get comfortable with, the UI is a bit intimidating for new users. SAP could organize their help better, it can be difficult to find dependable solutions to issues via their website and support channels. Read full review Likelihood to Renew Capacity of computing data in cluster and fast speed.
Steven Li Senior Software Developer (Consultant)
Read full review The institution has decided to move in a different direction, and will be using MSBI for reporting. I have been very happy with the Business Objects suite of tools, and will continue to use them heavily until we make the transition.
Read full review Usability The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.
Read full review From a server and client side perspective. the Business Intelligence Platform provides a foundation for all aspects of content development, distribution, analysis, collaboration and self service. Ease of use from targeted content delivery through controlled accessibility. Content exporting in the format of the users choice. Scheduling for internal or external delivery. Public and private folders for secure content access when requied. Web based for viewing on the users device of choice without the need to download additional applications.
Read full review Reliability and Availability When we implemented 3.1, we had a tough time managing the system: It took almost a year to stabilize. With 4.0, we want to roll out to more users, and are holding back because of fears about the performance issue
Read full review Performance Overall, the tool (Web Intelligence 4.2) is fast and solid. One issue is a dependability on JAVA for a full feature report creation/edit capabilities (as opposed to limited HTML option). Second, planned end of JAVA support by major browsers (Chrome is already not supporting JAVA applet).
Read full review Support Rating 1. It integrates very well with scala or python. 2. It's very easy to understand SQL interoperability. 3. Apache is way faster than the other competitive technologies. 4. The support from the Apache community is very huge for Spark. 5. Execution times are faster as compared to others. 6. There are a large number of forums available for Apache Spark. 7. The code availability for Apache Spark is simpler and easy to gain access to. 8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Read full review SAP has released various versions of SAP BO BI. starting from 3.1 and going to 4.0,4.1,4.2 and latest being 4.3. SAP provides support to these new versions. As new versions keep on coming, support for the very old software goes out of scope from SAP. it is when the different organization plans to get their BO content migrated from a lower version to a newer version. The newer version had definitely added functionality and features which ease the work of users.
Read full review In-Person Training SAP authorized training is best, Please go ahead with it. Even lot of online training options/videos available for self learning
Read full review Online Training I haven't used it or got feedback from the end user. Content looks to be pretty detailed. Focused on SQL but not BW.
Read full review Implementation Rating Hire specialists and experienced staff. Mix some beginners so that everyone is not a leader but a learner too. Plan well; architect well; break down implementation in small steps and move towards larger steps. Create a centralized and authorized SAP Business Objects implementation team.
Read full review Alternatives Considered All the above systems work quite well on big data transformations whereas Spark really shines with its bigger API support and its ability to read from and write to multiple data sources. Using Spark one can easily switch between declarative versus imperative versus functional type programming easily based on the situation. Also it doesn't need special data ingestion or indexing pre-processing like
Presto . Combining it with Jupyter Notebooks (
https://github.com/jupyter-incubator/sparkmagic ), one can develop the Spark code in an interactive manner in Scala or Python
Read full review We selected SAP BusinessObjects Business Intelligence (BI) based on price. It can stack up against others in terms of price and honestly, that's about it.
Salesforce Commerce does a hell of a better job at handling it. However, in the space of Business Intelligence, SAP can do more, and that's why at the end we went with it
Read full review Scalability SAP BusinessObjects Business Intelligence (BI) Platform supports SOA Service Oriented Architecture. You can start/restart/enable/disable all the servers. You can seamless do load balancing and clustering. It supports all leading application and web server. Supports LDAP SSO integration. People who can work on excel with training they can work on SAP Business Objects Web Intelligence, dashboard, Lumira, Information design tool product suite. Tool is very user friendly and easy to learn and implement
Read full review Return on Investment Faster turn around on feature development, we have seen a noticeable improvement in our agile development since using Spark. Easy adoption, having multiple departments use the same underlying technology even if the use cases are very different allows for more commonality amongst applications which definitely makes the operations team happy. Performance, we have been able to make some applications run over 20x faster since switching to Spark. This has saved us time, headaches, and operating costs. Read full review By generating and distributing reports in a timely manner, we were able to save millions of dollars for the company which otherwise would not have been visible. Almost realtime dashboard, saved the company a huge amount by showing the outages and kept the company from buying a tool to do just that. It showed the customers who were not paying the bills and were missing in the system due to some loophole. This was visible by doing reporting on the theft usage of electricity. Read full review ScreenShots