Microsoft's Azure Data Lake Analytics is a BI service for processing big data jobs without consideration for infrastructure.
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Infor Birst
Score 5.7 out of 10
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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.
Azure Data Lake Analytics services are beneficial when working with a lot of data. It can process enormous amounts of data extremely quickly. Service is secure and easy to set up, build, scale, and run on Azure. Regarding big data analytics and reporting, parallel processing has a significant impact. It consolidated our analytics from multiple systems and increased our analysis productivity. This tool has excellent support for reporting tools like Power BI and is very quick when performing analytics.
Infor Birst OEM and embedded analytics are well suited for advanced analytics and business intelligence. It has flexible deployment features and a lot of configuration ability with low code - no coding ability. Ability to ingest data from multiple live data sources. Source data from multiple sources can be segregated into multiple sections based on business criteria. Easily searchable business terms (metadata) across all enterprise analytic content.
End-to-end solution, from raw source data, ETL, warehousing and reporting, Birst is able to do everything we need in one package instead of needing to develop and maintain multiple technologies
Intuitive report development. The drag and drop creation of reports is simple. More complicated queries are easy to generate.
Very user-friendly and interactive. A lot of nice features are available both for developers and end users to streamline the process of preparing and consuming data
Rich API which allows us to programmatically interact with Birst
There's a bit of bias towards cloud with ADL Analytics. Depending upon a company's infra strategy and investment plans, there are some challenges with migration and integeration.
Not worth the time/effort/money if the organization doesn't have "Volume" of data. Cost effective only when daily loads exceed around 1million.
While training materials are available online, Adoption rate - Yet to pick up.
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.
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.
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.
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.
We did some research about Alibaba Cloud Data Lake Analytics and even being cheaper than Azure Data Lake Analytics, we decided to go for the second one once we noticed they have more features and better documentation. Another thing we considered during this process was the fact that we have more people that already have Azure Cloud knowledge.
Birst was better than Domo for our needs because we could get in and tinker with it. Our impression of Domo was that it had a lot of connectors and ready to go reports, but it made too many assumptions about applications we use. We customize too much to use a "ready to go" solution like that. When we looked at Tableau, we liked its visualization capabilities, but it wasn't going to help us do the extractions, ETL, and warehousing of data. It may have come some distance since then.
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.
