Infor Birst offers multi-tenant cloud BI for deployment in a public or private cloud, or on-premises. It provides an in-memory columnar data store and a BI layer comprising a reporting engine, predictive analytics tools, mobile native apps, dashboards, discovery tools, and an open client interface.
$30,000
Per 20 Users Per Year
Snowflake
Score 9.0 out of 10
N/A
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
Birst provide a much better web UI and end user experience and distribution mechanism than both Tableau and SSRS. Power BI simply did not have the full complement of features that we needed at the time of our selection to be competitive and Pentaho was too custom and would have …
Birst is well suited for an organization looking for a cloud-hosted analytics solution that is contained within one package. It is able to connect to a very wide variety of different data sources, and has options for either light or involved ETL procedures, depending on the users experience with preparing data. As with any BI project, it would not be suitable for an organization where there is no dedicated team to maintain and manage the project.
I am over our HR data, and we use Workday for our HR management system. I have a script in place that runs reports on Workday and saves the results as CSVs. I can then use stages in Snowflake to insert these CSVs into Snowflake, then I can insert or truncate and replace these staged tables into a final schema. Then once these are in a schema I can reference them and build out my data models. In addition to ingesting CSVs, Snowflake has the ability to write a CSV file to our Amazon S3 bucket. Ingesting these CSVs, transforming the data, then delivering it to a destination would've involved so much more coding than my current process if we were on any other platform.
Birst is an platform that provides connectors to some of the applications we use, but also allows us to bring in data from disparate systems to perform ETL and integrate all of the data for analyses. It makes no assumptions about your data, which is good for us, as we have a lot of customizations to many of our systems.
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
This tool is very much technical and proper knowledge is required, so mostly you have to hire an IT team.
I wish if various videos could be available for basic quires like its initiation, then I think it would act as a guideline and would help the beginners a lot.
We have been able to overcome any of the drawbacks we've found with Birst easily and it has fulfilled almost all of our analytic needs to date. Having seen their roadmap it would be highly unlikely we would move away from this platform any time soon. You simply can't beat the functionality that Birst provides for the price and the things I see coming out of the company solidify that our decision to choose Birst was the best possible choice. We have never regretted the decision.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
I would like to see additional usability put into the ETL scripting. Recently, Birst added a nice function reference inline to formula creation which has kept me from having to return to documentation so much. The same in ETL would be very beneficial. The interface problems related to the Flex framework are being addressed in a rewrite to HTML 5, but for now they are still a hindrance to a higher usability rating.
The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
We frequently experience -103 errors due to us using the Live Connect functionality, which does not seem to handle even minor interruptions in connectivity, and treats all future connection attempts or data requests as errors, even if the issue does not exist any longer
Everything runs very fast and smoothly. The only process that I wish was faster would be processing the data after uploading new data or making changes to the existing data model. It can take 15-20 minutes (roughly) to upload and process new data once you start getting into 10's of millions of rows. Given my experience with how long it takes me to pull the same data using SQL Server Management Studio, I don't think Birst is unreasonably slow - but for me to give a higher rating, I would want it to be unreasonably fast
When we have an issue that is stopping our business from proceeding, I want answers sooner than later. While Birst does have a published response time for each case level, we always wish it could be quicker. What response improvement could there be with a larger support team? In response to first question: Blackhole of issues - Birst needs to improve upon closing issues that resolution was dependent upon code fixes or enhancements, perhaps someone to add a comment on all case tickets at least every 60 days. Escalation - I always have the ability to electronically or via phone escalate a ticket. I also have my Customer Success Manager through whom I can escalate topics.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
I have attended two different training sessions. The first one was my initial training on the system. It was well paced, clear and concise. If there were questions that were not able to be answered by the instructor, he took down the question and actually followed up and provided us a response quickly. The second session was specific to the dashboard and report design components. This training was very good though there were some attendants who had little or no experience and their questions slowed the class.
Although I found the online resources helpful, a lack of appropriate examples for certain tasks key to report creation and advanced modeling make the online training/documentation less than perfect. For an inexperienced BI professional, the online training would not enable a streamlined launch of the product.
Have clean data! Birst flexibility allows - Start small, then introduce functionality and complexity along the way. If you try to present all the functionality [bells and whistles] and wow them, but bad data is uncovered, the end user blames the new application and turns away.
During the vetting process, we looked at 14 different products (one of them internal) to see if they would fit our needs and whittled it down to this one over a three month period. We did not contact sales for all of them (sales sites were enough to rule out some), but did have a lot of demos with a significant portion of them and reviewed several of the major industry studies as well. We had representatives of both user interests/design and the technical backend on the evaluation process.
The major features we were looking for a product that we could embed inside our own SaaS application, connect to a sharded Postgres database, had multitenancy and allowed for customer generated reports/ self-reporting. Some of the minor "nice to have" features we were looking at was scheduled reports, especially if we could plug it into our own scheduling system (for CAN-SPAM compliance), internationalization, and support.
In the evaluation, Birst hit all of the must-haves and enough of the nice to haves that they made it down to our final two and the trial was the clincher to make it our final choice.
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
we can see that loading a lot of data can cause a noticable slow down in performance. Birst support indicated that they don't really consider anything less than 30 seconds to be an issue, but that is not the case for our customers, so we have had to change some of implementation to address this
Being a manufacturing company we tend to lag behind technologically. But having all the data for different ERP systems in one place has been an eye opener for the executives. It has lessened the need to convert some legacy ERP systems.
Having such a simple reporting tool is a great asset to some of our sites that have traditionally had trouble gathering data from AS400 systems.
Positive impact: we use Snowflake to track our subscription and payment charges, which we use for internal and investor reporting
Positive impact: 3 times faster query speed compared to Treasure Data means that answers to stakeholders can be delivered quicker by analysts
Positive impact: recommender systems now source their data from Snowflake rather than Spark clusters, improving development speed, and no longer require maintainence of Spark clusters.
