IBM Planning Analytics, powered by IBM TM1®, is an integrated planning solution designed to promote collaboration across the organization and help keep pace with the speed of modern business. With its calculation engine, this enterprise performance management solution is designed to help users move beyond the limits of spreadsheets, automating the planning process to drive faster, more accurate results. Use it to unify data sources into one single repository, enabling users to build…
$825
per month 5 users
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.
Very powerful modeling capabilities. It has a really good OLAP engine memory. Strong scenario planning for what if analysis. Flexibility of integration with ERPs or WM systems for both cloud and on premises. Centralized planning and alignment of governance is also a plus. Having one single system for many different functions.
When data is in a system that needs a complex transformation to be usable for an average user. Such tasks as data residing in systems that have very different connection speeds. It can be integrated and used together after passing through the SAS Data Integration Studio removing timing issues from the users' worries. A part that is perhaps less appropriate is getting users who are not familiar with the source data to set up the load processes.
SAS/Access is great for manipulating large and complex databases.
SAS/Access makes it easy to format reports and graphics from your data.
Data Management and data storage using the Hadoop environment in SAS/Access allows for rapid analysis and simple programming language for all your data needs.
Since IBM Cognos Express is suitable only for medium data warehouse environment, we are not sure if this tool solves the long term need as the business keeps growing rapidly. So its a 50/50 ratio to renew Express license. But having said that, the components of IBM Cognos Express are also available in other Cognos BI suites like Cognos 10.x version. So we will probably upgrade our environment to IBM Cognos 10.x which comes with more new features.
IBM Planning Analytics is generally good in terms of functionalities. It can be used reduce time for budget planning, resource planning, demand forecasting, etc. The performance of IBM Planning Analytics is acceptable, but user interface can be improved. It would be good to see new features that allow users to customise the dashboard.
The main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
IBM support has been very quick to respond and handle the very few issues we've had. We've had a third-party who partners with IBM to be our consulting team which has helped greatly reduce the need for us to contact IBM directly. I highly recommend researching and selecting a well-respected partner to help with an implementation as well as ongoing support as needed.
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
As it is related to MS Excel, IBM Planning Analytics is a much more robust and complete solution for the CFO or COO in mind. Oracle Hyperion stacks up nicely against IBM Planning Analytics. However, IBM's investment in AI allows Planning Analytics users more options and speed.
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.