Showing posts with label Data Analysis. Show all posts
Showing posts with label Data Analysis. Show all posts

Thursday, November 17, 2016

Power in BI = Power BI

Many times decisions are based upon existing Features. 'The Only Thing That Is Constant Is Change', we do not want to base a decision on existing product features. When comparing we take into consideration how other competitive products/services are evolving. Are they adding new features? How frequently?

Tableau and Qlik historically had lead over Power BI in Data Visualization. I am now convinced that Power BI has the edge over others, here is the Gartner BI and Analytics magic quadrant report which ranks Power BI as visionary.

This is why I believe Power BI has edge over other

1. Organizations uses on an average '13' apps (data sources) - Okta Research finding

Which applies, a business analyst will have at least 13 tables joins to make a meaningful story. He/she has to slog (to understand the tables/views/relationships) if there is content pack, to get data from source. There are plenty of app connectors available on all three tools- Power BI, Tableau and Qlik. Power BI has more app connectors than others, you can quickly and easily get the required data from apps. Microsoft has understood the  importance of participating in open source, as it has officially joined the Linux foundation today. Not only it has connections to existing Microsoft stack (cloud/on premise), but also other others - Salesforce, Google Analytics, Github and many others. 

2. We need to store the data before consuming it, need to save data in SQL and other formats

ETL will be more relevant than ever before, to make a sense from multiple data sources - a good (join) relationship is required. Tableau and Qlik can read files and other data source, but they lack the ETL layer. Microsoft stack (SQL, Azure SQL and others) provides tools to transform and save the data in SQL and other formats. The complex transformation can Microsoft stack, leaving the light transformation to Power BI. Power BI as a part of Microsoft family has tremendous advantage.

3. Price, Price, Price

Look no further. At $9.99/Month is the Power BI pro version, the least expensive of the all products.


There are features which Power BI lacks currently - as discussed here by Tableau. This features comparison will not be relevant in the future, Power BI will catch up quickly. For some scenarios maybe Power BI is not the best Data Visualization tool. As a generalist which most of us are, we will find Power BI to be flexible, powerful and affordable.

Monday, May 20, 2013

Google BigQuery, SAP HANA- Cloud Solutions

Week of May 13th, 2013 was a big deal for SAP and Google. Two major events were held-SAPHIRE in Orlando and Developer I/O 2013 in San Francisco. 

I was lucky to get a Google I/O 2013 ticket, and be on of the 6000 participants. My objective was to learn about Google BigQuery and Google Apps Script.

Both companies are competitors in Cloud based 'Analysis or massive database' , SAP HANA has two product versions 'Appliance ' (Hardware and Software) and 'Cloud'. Where as Google has Cloud solution BigQuery. 

SWOT
SAP HANA Appliance
SAP HANA Cloud
Google BigQuery
Strengths
- Strong SAP Products/Branding
- No downtime
- Good for Ad hoc requirements
- Good Enterprise Cloud offerings
- No downtime
- Good for Ad hoc requirements
- Good Developer community
Weakness
- Maybe costs and downtime
- Dependency on AWA (Amazon web services) for cloud storage
- Provides tools, not business suits
- some products are evolving (e.g. Data Visualization)
Opportunities
- Increase production adoption
- Conversion from Cloud version
- Use as database for other applications
- Use as database for other applications
- Convert clients with web security concerns
- Encourage Developer community to build solutions
- Use as database for other applications (using Compute Engine)
- Convert clients with web security concerns
Threats
- Cloud products, and other Appliances
- Google BigQuery, Maybe Amazon
- Maybe Amazon


There were two client presentations on BigQuery - Gamesys and Shutterfly, these clients also use Google Apps Script for data visualization/reporting.

Here are the two Google BigQuery recordings
Big Data Mashups: Enabling Next Generation Analytics Using BigQuery
Here Be BigQuery: Building Social Gaming Infrastructure on the Google Cloud Platform

Another interesting project was All the Ships in the World: Visualizing Data with Google Cloud and Maps, which integrate many Google technologies to visualize real time Data.

I see SAP ideologically now being more open, proving more resources to developers and planning more Cloud based products.

It will be interesting to see how enterprise Cloud database and analysis tools will evolve and their acceptance.

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