Apache Spark vs. SAP BusinessObjects Business Intelligence

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.

Incentivized

As mentioned earlier reporting was a big headache for us and the tools we used didn't support large data sets and visualization Performing analytics with such data sets was cumbersome and later post using this SAP BusinessObjects Business Intelligence we were able to correlate different data sets and prepare the dashboard pretty easier which were helpful and easier to understand.

Incentivized

• Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
• Faster in execution times compare to Hadoop and PIG Latin
• Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
• Interoperability between SQL and Scala / Python style of munging data

Incentivized

• 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.

Incentivized

• 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

Incentivized

• 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.

Incentivized

Capacity of computing data in cluster and fast speed.

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.

Incentivized

If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used

Incentivized

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.

Incentivized

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

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).

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.

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.

Incentivized

SAP authorized training is best, Please go ahead with it. Even lot of online training options/videos available for self learning

Incentivized

I haven't used it or got feedback from the end user.

Content looks to be pretty detailed. Focused on SQL but not BW.

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.

Incentivized

Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.

Incentivized

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

Incentivized

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

Incentivized

• Business leaders are able to take data driven decisions
• Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
• Business is able come up with new product ideas

Incentivized

• 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.

Incentivized