Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.
$0
per month
Power BI For Office 365 (discontinued)
Score 8.4 out of 10
N/A
Power BI for Office 365 allowed users to model and analyze data, and query large datasets with complex natural language queries. It has been discontinued in favor of other editions of Power BI going forward.
ANACONDA VS Alteryx Analytics: Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics.
I prefer Anaconda due to the control I have at every level over the data and the visualizations. Power BI does a better job at guessing what graphics to use, but these usually aren't the most helpful. Anaconda and the slew of Python extensions that add incredible functionality, …
I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.
If you're already using Office 365, Power BI for O365 is an easy choice. Start playing around with the free version and then easily add individual Pro licenses with little risk. However, if you anticipate using this with many users, it can get expensive quickly.
Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.
Easy to make visual dashboards from SQL queries. Previously we had to use a third party application that had to run on a web server that was so complex to setup and run. PowerBI removes all that.
Ability to control who/which group has access to each dashboard or report. Ties in well with the rest of the Office 365 ecosystem.
Has many connectors to allow pulling data from various systems, both onsite (via gateway) or external (via APIs), and join the data to create a report/dashboard.
Ability to show data but also export the data, if permitted.
Easy to show PowerBI dashboards on SharePoint or on other websites via embedded code.
I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.
Licensing: Currently, Microsoft has a fixed pricing model for Office 365 users, regardless of role/function of the user. Most organizations have a small number of "power users" that create usable content and many more "consumers" that simply view/run reports created by power users. Microsoft does not differentiate between these users, and thus the pricing limits organizations from large deployments of the software.
Version incompatibility: Excel 2010 and 2013 workbooks are compatible with each other. However, workbooks created in 2010 that include PowerPivot databases must be upgraded to 2013 format to run in 2013. Subsequently, you cannot open these upgraded PowerPivot workbooks in 2010. This requires ALL users to be on the same version.
Visualization: Excel charting with PowerPivot workbooks is adequate for many users. Power View also contains a number of GREAT visualizations, including animated bubble charts and a very flexible dashboard/report design canvas. However, compared to some of the other self-service BI solutions, it is still limited in its visualization capabilities.
It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
I will continue to recommend this suite to folks looking for a reporting and analytics solution, as I find in MOST cases, it's great at meeting almost every requirement I've been given by a multitude of clients across a range of industries. I've built Capacity Planning solutions that allowed end user input which was then submitted to SharePoint, Executive Dashboards, custom applications, simple analytical tools for teams to easily slice and dice data, and super simple reports as well as some very complicated ones. If you haven't seen the demos online, do a search, and see for yourself - this is a great BI suite! (I do not work for Microsoft, although I do consult out there from time to time. I do occasionally make a recommendation for a different BI reporting tool, but in general, find Excel can accomplish quite a bit for less money and in less time.)
I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.
We are satisfied with the functionality and capabilities of Power BI. Product is cost effective and full-fill the reporting requirements of the organization. You can perform most of the report level complex analysis with the help of DAX which makes Power BI very powerful analytic tool. Power BI for Office 365 has gone away and Power BI is the next evolution of it. Power BI comes with your Office 365 E5 subscription or you can purchase licensing for it separately.
Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
as of now there is strong community for Power BI, you can get solution for most of your problems from there. Also you can send your error to Microsoft as well. After every 15 days they release updates to overcome all the issues of defects.
I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!
Oracle was nice, super expensive to implement if it's not in use already. JobDiva is choppy and heavy on the system while does not give great reports. Salesforce is good; remote access is good however their support is terrible
It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.
As a Microsoft Partner implementing Business Intelligence solutions, Power BI has removed the barrier for our clients to begin the "BI journey". So often, projects get hung up in that early phase of procuring and installing/configuring expensive hardware and software. Just simply getting started and designing a beginning solution has allowed our clients to see results in 1-2 weeks using their data that might have taken months to achieve otherwise.
One significant ROI example is process improvement. In many cases, individuals or teams are spending days each month gathering data from multiple sources for reporting to their constituents. We are reducing these times to minutes by automating many of the data collection and integration processes that were previously manual.
