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102 Ratings

Microsoft BI

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628 Ratings
102 Ratings
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Score 8.5 out of 101

Microsoft BI

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628 Ratings
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Score 7.9 out of 101

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Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
Thomas Young profile photo

Microsoft BI

Most suitable scenarios:
-Large scale report automation and distribution.
-Self service BI for internal and external users.
-Relational databases and multidimensional models.
-Comprehensive security & access control.

Less appropriate scenarios:
-Non-relational databases
-Low budget
-Tight timeframe

I'd invite anyone reading this far to think hard on his/her goals with BI. Are you trying to build a solid and endurable BI service for your clients or your own organisation? Or do you just need to have some quick visualisation of the data you have to make strategic or operational decisions in a few weeks time?

Implementing a MicrosoftS BI stack takes time, knowledge, and skills, none of these comes cheaply these days. If your answer to my first question is "yes", go ahead and study Microsoft BI a bit more then make your decision on your own. If you see my second question is most relevant to you, go and grab a web-based BI tool such as SiSense, Tableau, Splunk, and so on. Take the free trial option and see if you can test your ideas fast and at a lower cost. Good luck!
Haibo Yang profile photo

Feature Rating Comparison

BI Standard Reporting

Apache Spark
Microsoft BI
8.0
Pixel Perfect reports
Apache Spark
Microsoft BI
7.9
Customizable dashboards
Apache Spark
Microsoft BI
7.9
Report Formatting Templates
Apache Spark
Microsoft BI
8.2

Ad-hoc Reporting

Apache Spark
Microsoft BI
8.4
Drill-down analysis
Apache Spark
Microsoft BI
8.2
Formatting capabilities
Apache Spark
Microsoft BI
8.4
Integration with R or other statistical packages
Apache Spark
Microsoft BI
8.2
Report sharing and collaboration
Apache Spark
Microsoft BI
8.9

Report Output and Scheduling

Apache Spark
Microsoft BI
8.2
Publish to Web
Apache Spark
Microsoft BI
8.3
Publish to PDF
Apache Spark
Microsoft BI
8.8
Report Versioning
Apache Spark
Microsoft BI
8.2
Report Delivery Scheduling
Apache Spark
Microsoft BI
7.6
Delivery to Remote Servers
Apache Spark
Microsoft BI
8.2

Data Discovery and Visualization

Apache Spark
Microsoft BI
8.2
Pre-built visualization formats (heatmaps, scatter plots etc.)
Apache Spark
Microsoft BI
8.5
Location Analytics / Geographic Visualization
Apache Spark
Microsoft BI
8.0
Predictive Analytics
Apache Spark
Microsoft BI
8.1

Access Control and Security

Apache Spark
Microsoft BI
8.4
Multi-User Support (named login)
Apache Spark
Microsoft BI
8.4
Role-Based Security Model
Apache Spark
Microsoft BI
8.2
Multiple Access Permission Levels (Create, Read, Delete)
Apache Spark
Microsoft BI
8.6
Single Sign-On (SSO)
Apache Spark
Microsoft BI
8.4

Mobile Capabilities

Apache Spark
Microsoft BI
8.3
Responsive Design for Web Access
Apache Spark
Microsoft BI
8.2
Dedicated iOS Application
Apache Spark
Microsoft BI
8.4
Dedicated Android Application
Apache Spark
Microsoft BI
8.1
Dashboard / Report / Visualization Interactivity on Mobile
Apache Spark
Microsoft BI
8.2

Application Program Interfaces (APIs) / Embedding

Apache Spark
Microsoft BI
7.9
REST API
Apache Spark
Microsoft BI
7.9
Javascript API
Apache Spark
Microsoft BI
8.3
iFrames
Apache Spark
Microsoft BI
7.8
Java API
Apache Spark
Microsoft BI
7.6
Themeable User Interface (UI)
Apache Spark
Microsoft BI
7.9
Customizable Platform (Open Source)
Apache Spark
Microsoft BI
7.6

Pros

  • Apache Spark makes processing very large data sets possible. It handles these data sets in a fairly quick manner.
  • Apache Spark does a fairly good job implementing machine learning models for larger data sets.
  • Apache Spark seems to be a rapidly advancing software, with the new features making the software ever more straight-forward to use.
Thomas Young profile photo
  • Connecting andJoining Multiple Data Sources Together - Multi-Dimensional SSAS
  • Usability in Report Creation for Business Analysts (Excel via Analysis Services specifically), Executives (Performance Point and Power BI) and Power Users (Report Builder)
  • Collaboration (via SharePoint only, before the release of Power BI Designer)
  • Speed of Analysis - Specifically when leveraging SSAS on databases up to 5 TB
  • Speed of ETL processing - Multiple Parallel Sequential Jobs with SSIS/DTS
Lee Cullom profile photo

Cons

  • Apache Spark requires some advanced ability to understand and structure the modeling of big data. The software is not user-friendly.
  • The graphics produced by Apache Spark are by no means world-class. They sometimes appear high-schoolish.
  • Apache Spark takes an enormous amount of time to crunch through multiple nodes across very large data sets. Apache Spark could improve this by offering the software in a more interactive programming environment.
Thomas Young profile photo
  • SQL Server Data Integration (also knows as SSIS) seems to provide most functionality you would expect from an ETL tool. However, when you start using it you quickly find out that most transformations perform slower than equivalent functionality when coded directly in SQL. So you go ahead with creating joins, using case statements and data type conversions directly in SQL input statements and potentially end up with a huge piece of code that performs nicely but is hardly maintainable in the future.
  • The development environment takes quite a while to get used to. Once you are all set up and doing your development work it is all fine but if you accidentally close some window or 'pane' just figuring out how to get it back can take quite some time.
Julia Gusman profile photo

Likelihood to Renew

No score
No answers yet
No answers on this topic
Microsoft BI8.0
Based on 25 answers
Low Cost and catching up to the market expectations
No photo available

Usability

No score
No answers yet
No answers on this topic
Microsoft BI7.0
Based on 5 answers
It's a good rating for people willing to learn and get used to it, but it's not inherently user friendly, especially to people who are not Excel power users.
Alexander Lubyansky profile photo

Reliability and Availability

No score
No answers yet
No answers on this topic
Microsoft BI9.5
Based on 2 answers
The product has been reliable.
Robert Goodman profile photo

Performance

No score
No answers yet
No answers on this topic
Microsoft BI7.0
Based on 2 answers
SQL Server Reporting Services (SSRS) can drag at times. We created two report servers and placed them under an F5 load balancer. This configuration has worked well. We have seen sluggish performance at times due to the Windows Firewall.
Robert Goodman profile photo

Support

No score
No answers yet
No answers on this topic
Microsoft BI7.1
Based on 6 answers
I am basing this rating not on Microsoft's paid premium support, but rather on the resources available (both from Microsoft and 3rd parties) to BI consumers. There is such a huge community working with and building solutions with the Microsoft BI stack (SQL Server) that I have always been able to find a solution (or at least a workaround) to any problems that have come up.
Sean Brady profile photo

In-Person Training

No score
No answers yet
No answers on this topic
Microsoft BI6.9
Based on 3 answers
This training was more directed toward what the product was capable of rather than actual programming.
Stephanie Grice profile photo

Online Training

No score
No answers yet
No answers on this topic
Microsoft BI8.5
Based on 2 answers
I have used on-line training from Microsoft and from Pragmatic Works. I would recommend Pragmatic Works as the best way to get up to speed quickly, and then use the Microsoft on-line training to deep dive into specific features that you need to get depth with.
Sean Brady profile photo

Implementation

No score
No answers yet
No answers on this topic
Microsoft BI9.6
Based on 7 answers
Thorough project planning and requirements gathering ensured project's success.
Boris Skylar profile photo

Alternatives Considered

All the above systems work quite well on big data transformations whereas Spark really shines with its bigger API support and its ability to read from and write to multiple data sources. Using Spark one can easily switch between declarative versus imperative versus functional type programming easily based on the situation. Also it doesn't need special data ingestion or indexing pre-processing like Presto. Combining it with Jupyter Notebooks (https://github.com/jupyter-incubator/sparkmagic), one can develop the Spark code in an interactive manner in Scala or Python
Nitin Pasumarthy profile photo
With over 20 years in IT, I have experienced a full range of relational and non-relational data solutions, from Oracle and Informix to MongoDB and Hadoop. In my opinion, the Microsoft BI stack is the most complete, well-rounded, high performing data management system on the planet right now. More and more, the ability to make data-driven decisions sets organizations apart from their competitors, and no one offers a better solution than Microsoft and its partners. As more and more of what we do in business life moves to the cloud, Microsoft is again leading the way with its Azure platforms.
Chris Utter profile photo

Return on Investment

  • Workflow process using spark went from 1 day to 2 hours
  • Spark Streaming allowed for quick determiniation of data validity
  • spark on yarn was good for manangement. But Spark with Kubernetes was easier to use.
Anson Abraham profile photo
  • Business users easily learned self service BI with training and what to do and what not to do with self service BI
  • Learning curve for Powerpivot and other office 365 tools for IT team who already knew about data warehousing concepts is steep
No photo available

Pricing Details

Apache Spark

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Apache Spark Editions & Modules
Apache Spark
Additional Pricing Details

Microsoft BI

General
Free Trial
Free/Freemium Version
Yes
Premium Consulting/Integration Services
Entry-level set up fee?
No
Microsoft BI Editions & Modules
Microsoft BI
Edition
Power BI
$0
Power BI Pro
$102
2. per user per month
Additional Pricing Details