Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
SAP BusinessObjects Business Intelligence
Score 7.4 out of 10
N/A
The SAP® BusinessObjects™ Business Intelligence Platform provides users with ad hoc queries, reporting, data visualizations, and analysis tools. Its integrated, unified infrastructure aims to offer scalability from one-to-many tools and interfaces on-premise, in the cloud, or as a hybrid approach.
N/A
Pricing
Google BigQuery
SAP BusinessObjects Business Intelligence
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
No answers on this topic
Offerings
Pricing Offerings
Google BigQuery
SAP BusinessObjects Business Intelligence
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Google BigQuery
SAP BusinessObjects Business Intelligence
Features
Google BigQuery
SAP BusinessObjects Business Intelligence
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google BigQuery
8.5
80 Ratings
0% below category average
SAP BusinessObjects Business Intelligence
-
Ratings
Automatic software patching
8.017 Ratings
00 Ratings
Database scalability
9.179 Ratings
00 Ratings
Automated backups
8.524 Ratings
00 Ratings
Database security provisions
8.773 Ratings
00 Ratings
Monitoring and metrics
8.475 Ratings
00 Ratings
Automatic host deployment
8.013 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Google BigQuery
-
Ratings
SAP BusinessObjects Business Intelligence
8.0
55 Ratings
2% below category average
Pixel Perfect reports
00 Ratings
8.649 Ratings
Customizable dashboards
00 Ratings
7.651 Ratings
Report Formatting Templates
00 Ratings
7.951 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Google BigQuery
-
Ratings
SAP BusinessObjects Business Intelligence
7.4
52 Ratings
8% below category average
Drill-down analysis
00 Ratings
7.151 Ratings
Formatting capabilities
00 Ratings
7.250 Ratings
Integration with R or other statistical packages
00 Ratings
7.935 Ratings
Report sharing and collaboration
00 Ratings
7.651 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Google BigQuery
-
Ratings
SAP BusinessObjects Business Intelligence
8.0
52 Ratings
3% below category average
Publish to Web
00 Ratings
8.843 Ratings
Publish to PDF
00 Ratings
8.250 Ratings
Report Versioning
00 Ratings
7.345 Ratings
Report Delivery Scheduling
00 Ratings
8.351 Ratings
Delivery to Remote Servers
00 Ratings
7.430 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
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.
GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
Seamless integration with other GCP products.
A simple pipeline might look like this:-
GForms -> GSheets -> BigQuery -> Looker
It all links up really well and with ease.
One instance holds many projects.
Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
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.
Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
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.
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
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.
I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
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.
I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
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).
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
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.
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.
PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
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
We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
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
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
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.