Asset (Volunteers, Field offices & Equipments) management & planning for a global crisis response team.
Working in a team, we created statistical surveys for field works to collect data about current state & estimated future needs. We also helped them with data gathering & cleaning tasks. After that, we helped them analyze & visualize the data to find actions for executives leading the global crisis response team.
Here’s a mockup of one of the ten data visualization created for them:
This post is a quick summary for all Business Analytics related updates that I saw at PASS Summit’14:
1. Theme of the Keynote(s)/Session(s) seemed to be around educating the community about the benefits of the NEW(er) tools. I saw demos/material for cloud-based tools like SQL databases, Azure stream analytics, Azure DocumentDB, AzureHDInsight & Azure Machine learning. The core message was pretty clear: A data professional does two things – 1) Guards data OR 2) helps to generate Insights from Data – And they will need to keep up-to-date on the new tools to future-proof their career.
Read more about this here: http://blogs.technet.com/b/dataplatforminsider/archive/2014/11/05/microsoft-announces-major-update-to-azure-sql-database-adds-free-tier-to-azure-machine-learning.aspx
2. Coming soon: Power BI will be able to connect to on-premise SSAS data sources (multi-dim & tabular).
3. Coming soon: A better experience to create Power BI dashboards.
Read more about Power BI updates here: http://www.jenunderwood.com/2014/11/05/pass-summit-2014-bi-news/
4. Azure Machine Learning adds a free-tier! You won’t need a credit-card/subscription to sign up for this.
5. I also saw sessions proposing new way of thinking about an architecture for “Self Service BI” and “Big Data” which might be worth following because since these are newer tools, it’s definitely worth considering an architecture that’s designed to make the most of the investments in these new tools. That’s it & I’ll leave you with a quote from James Phillips from Day 1’s keynote:
Need a daily report delivered in sales team’s inbox that shows Sales Team’s Bookings vs Quota for current & next month.
Ability to see Bookings vs Quota in near real-time is a key to effectively manage performance for any sales team. Before the project, analyst(s) would have to manually put together this report and since the report took more than a day to put together they couldn’t afford to run it daily and so they delivered this report bi-weekly/monthly basis to the sales team. After the project, the process was automated and the sales team received an email with a report on a daily basis and this helped them see Bookings vs Quota in near real-time. As a famous saying goes “if you can’t measure it, you can’t improve it” (by Peter Drucker) – in this case, the report helped them measure their actual numbers against their goals and helping them improve their sales numbers which directly hits their top-line!
Tools used: SharePoint report subscription, SQL server analysis services, SQL Server Integration services, SQL server reporting services & Excel.
Note: Drill down reports are not shown and the numbers are made up.
Internet enabled computers to be connected with each other.
Internet enabled Mobile Devices to be connected with each other.
Now, Internet will be used to enable physical things to be connected with each other. This is what is called “Internet of things” (IoT).
So what happens?
since more devices are connected with internet – we will able to generate more data! This is usually good if there’s a business vision around how to make sense of data to increase efficiency of all these things.
Here’s a nice case study from Microsoft (focus on the business case – the things in this case is “elevator” to drive reliability)
This is all good news for data professionals! There will be increased demand for professionals who can help businesses make sense of data generated via IoT.
Also beware of the “hype” around this technology. It’s important to take incremental steps to achieve the vision – Instead of trying to analyze data from ALL devices in your organization, start with one physical thing that matter the most for your organization or start with data that you have and take incremental steps to spread data culture in your organization!
Now that Big Data has become a mainstream word in IT and business, we have a new buzzword to learn/talk about IoT – but remember it’s all about making sense of data and your skills would be more valuable than ever!
Need to understand the patterns in Quality test results data across all plants.
- The solution involved creating a Business Intelligence system that gathered data from multiple plants. I was involved in mentoring IT team, development and end-user training of a Business Intelligence Dashboard that used SQL server analysis services as it’s data source.
- Dashboard development involved multiple checkpoint meetings with business leaders since this was the first time they had a chance to visualize quality test results data consolidated from multiple plants. Since they were new to data visualization, I used to prepare in advance and create 3-4 relevant visualization templates to kick off meetings.
(it is intended to look generic since I can’t discuss details. Also, drill down capabilities had been added to the dashboard to go down to the lowest granularity if needed)
To test my Tableau knowledge, I attempted the Tableau product certification and got the “Tableau Desktop 8 Qualified Associate” certificate.
Take a look at the following chart, do you see any issues with it?
Notice that the month values are shown as “distinct” values instead of shown as a “continuous” values and it misleads the person looking at the chart. Agree? Great! You already know based on your instincts what continuous and discrete values are, it’s just that we will need to label what you already know.
In the example used above, the “Date & Time” shown as a “Sales Date” is a continuous value since you can’t never say the “Exact” time that the event occurred…1/1/2008 22 hours, 15 minutes, 7 seconds, 5 milliseconds…and it goes on…it’s continuous.
But let’s say you wanted to see Number of Units Sold Vs Product Name. now that’s countable, isn’t it? You can say that we sold 150 units of Product X and 250 units of product Y. In this case, Units sold becomes discrete value.
The chart shown above was treating Sales Date as discrete values and hence causing confusion…let’s fix it since now you the difference between continuous and discrete variables:
To develop effective data visualizations, it’s important to understand the data types of your data. In this post, you saw the difference between continuous and discrete variables and their importance in data visualization.