How to fix the Non-unicode to unicode data type conversion problems in SQL Server Integration Services?



Are you trying to import an Excel file into SQL Server using SQL Server Integration services…And ran into error that has words like “Non unicode” and “unicode”? Then this blog is for you.

Why does this error occur?

Well it turns out that things like SQL Server and Excel have encoding standards that they follow which provides them a way to process, exchange & store data. BUT turns out that SQL Server and Excel use different standards.


So, the solution is simple right? Import the data from Excel into non-Unicode format because that’s what you need for SQL Server.

So how do you that? Between your Source and Destination tasks, include a task called “Data conversion” and do the following for all columns that have text:

Excel SQL Server Unicode Nonunicode

And in the destination task, you’ll have to make sure that the mapping section using the new output aliases that you defined in the “data conversion” step.


In this post, we learned about how to solve a common error that pops up when you try to import excel file to sql server using SSIS. Hope that helps.

Author: Paras Doshi

How to add Sparkline data visualization to Google spread sheets?


I like using spark lines data viz when it makes sense! It’s a great way to visualize trends in the data without taking too much space. Now, I knew how to add sparklines in Excel but recently, I wanted to use that on Google sheet and I had to figure it out so here are my notes:

1. Google has an inbuilt function called “SPARKLINE” to do this.

2. Sample usage: =SPARKLINE(B2:G2) — by default you can put line chart in your cells.

3. Then there are other options including changing the chart type. You can find them documented here:

4. One of the best practices that I advocate when you spark-line to “compare” trends is to make sure that you have the consistent axis definition. So the sample usage for that could like this:


(if you want to do this for excel then here’s the post: )

After you’re done, here’s what a finished version could like on Google sheet:

Google Sheet Data visualization spark line

Here’s the working google sheet:

How to assign same axis values to a group of spark-lines in Excel?


Spark-line is a very handy data visualization technique! It’s great when you are space constrained to show trends among multiple data points.

Here’s an example:

Spark Line Trend Excel Data Visualization

But there’s an issue with above chart! Axis values for these group of spark-lines do not seem match – it could throw someone off if they didn’t pay close attention. So a good practice – when you know users are going to compare segments based on the spark-lines – is to assign them same axis values so it’s easier to compare. Here’s the modified version:

Excel Sparkline data visualization same axis

And…here are the steps:

1. Make sure that spark-lines are grouped.

Select the spark-lines > go to toolbar > Sparkline Tools > Design > Group

Excel Sparkline Group

2. On the “group” section, you’ll also find the “Axis” option – select that and make sure that “same for all axis” is selected for Vertical axis minimum and maximum values:

Excel Spark Line Data Viz same min max value


That’s about it. Just a quick formatting option that makes your spark-lines much more effective!

Author: Paras Doshi

Every Data Analyst Needs to check out this FREE excel add-in: Power Query!


Power Query is amazing! It takes the data analysis capabilities of Excel to whole new level! In this post, I am going to share three reasons:

1. it enables repeatable mash-up of data!

Have you every had to do your data analysis tasks repeatedly on the data with same structure? Do you get “new” data every other week and need to go through the same data transformation workflow to get to the data that you need?

What’s the solution? Well, you can look at MACRO’s! Or you can request your IT department to create a Business Intelligence platform. However, what if you need to modify your data mashup workflow then these solutions don’t look great, do they now?

Don’t worry! Power Query is here!

It enables repeatable mashup of data like you might have never seen before! You need to try it to believe.

It’s very easy to input new data to Power Query and it enables you to retrieve final output based on new data using a “refresh” feature.

Each data-mashup is recorded as steps which you can go back and edit if you need to.

Power Query Refresh

2. It’s super-flexible!

Any data mashup performed using Power Query is expressed using its formula language called “M”. You can edit the code if you need to and as you can imagine such a platform enables much-needed flexibility for the analyst’s.

3. It has awesome advance features!

Do you want to Merge data? How about Join? Are you tired with VLOOKUP’s! Don’t worry! it’s super easy with Power Query! Here’s a post: Join Excel Tables in Power Query

How about Pivot or Unpivot? Done! Check this out: Unpivot excel data using Power Query

How about searching for online & open data sets? Done!

How about connecting to data sources that “Data” section of Excel doesn’t support yet? (Example: Facebook) – DONE! Power Query makes that happen for you.

And That’s not a complete list!

Plus you can unlock the “Power” (pun intended) of Power Query by using it with other tools in Power BI Stack. (Power Pivot, Power View, etc…) OR you can use the your final output from Power Query with other tools too! After all it’s an excel file.


If you haven’t already then check out Power Query! it’s free and works with Excel 2010 and above.

Author: Paras Doshi

Live tweeted #sqlpass’s Business Analytics VC webinar: 13 Excel Tips!


I was live tweeting during our monthly PASS Business Analytics VC meeting, Here are the tweets to learn about 13 Excel Tips!

Thanks everyone who attended, I hope it was helpful!

Here are some ways to follow the Virtual Chapter:

News from PASS Summit’14 for Business Analytics Professionals: #sqlpass #summit14


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:

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:

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:

How to get descriptive statistics in Excel?



you are analyzing a dataset and before modeling/analyzing you need to generate descriptive statistics on a field. you have the data loaded in Excel and wondered if there’s a way to do that in Excel.


There’s an out of the box solution that will support your needs to generate descriptive statistics on a field. Here are the steps:

Note: for the purpose of this blog post, I am using Excel 2013 but data analysis toolpak is available in Excel 2007+.

1. Active “Data Analysis” toolpak.

Follow this steps:  File > Options > Add-ins > Manage: Excel Addins > “GO”

excel data analysis toolpak

2. make sure to check the “analysis toolpak” checkbox.

3. Now you should see a “data analysis” option under the “Data” pane:

Excel Data Analysis Descriptive Statistics

4. Now click on “Data Analysis” and select one of the following options:

Anova, Correlation, Covariance, Descriptive Statistics, Exponential Smoothing, F-Test Two-Sample for Variances, Fourier Analysis, Histogram, Moving Average, Random Number Generation, Rank and Percentile, Regression, Sampling, t-Test, z-Test.

in this case, let’s go with descriptive statistics but you can see that you can perform other tasks as well.

5. Once you click on the descriptive statistics, a dialog box will show up and you will have to enter some data like your input range to generate descriptive statistics. Once you have filled the data needed, click on OK and it should generate descriptive statistics for you in EXCEL!

I hope that helps!


In this post, we saw how to generate descriptive statistics in Microsoft Excel.

Author: Paras Doshi

Cost Driver’s Dashboard for a Supply Chain Executive:

Supply Chain Cost Drivers Profitability Dashboard


Profitability equals revenue minus costs – To that end, A supply chain executive is mostly focused on optimizing cost elements to drive profitability. Here’s a mock up of a dashboard created for an executive to help him keep an eye on the overall health while making sure he gets alerted for key cost categories.

The Dashboard was created using profitability data-set & also had drill down capabilities to analyze numbers for cost buckets like Raw materials, manufacturing & logistics.


Supply Chain Cost Drivers Profitability Dashboard

Power Pivot: How to get Month Name from a date field?



How do you get a Month Name from a date field in Power Pivot?


here’s a code snippet that should help:


This should give you month names (Jan, Feb, …) instead of integers that are returned by the MONTH function.

couple of notes:

1. date field needs to be used to get the month name

2. MMM needs to be in uppercase.

I hope this helps.

Back to basics: continuous Vs. Discrete variables and their importance in Data Visualization.


Take a look at the following chart, do you see any issues with it?

month trend chart line chart string to date

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:

Statistics Discrete Continuos Variable Data Visualization


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.