In our recent posts, we’ve been looking at how Ask Zia can empower you to extract powerful insights from your data in minutes. You can ask Zia any question about your business and get instant answers in the form of KPIs and reports. Sales, Marketing, Finance, Help Desk, Social Media, eCommerce, and more—Zia can interpret your data from any business domain and provide you with meaningful insights.
Since businesses vary, terms and conventions will too. Being an NLP (natural language processing) system, Zia may sometimes have trouble understanding your domain and business-specific terms.
So, how do you handle these situations?
This is where Zia’s customization and adaptability come into play. You can train Zia to learn and adapt to your domain-specific conventions and phrases in minutes. In this post, we’ll see how we can train and customize Zia to fit your exact business needs.
The customization options in Zia can be grouped into three categories:
- Column Priority
- Default Function
A synonym, as we all know, is a word or phrase that means something similar to another word. When you ask Zia a question, the business term you use may differ from the column name Zia can fetch data from. To avoid any confusion, you can map these two terms by defining synonyms.
For example, in a sales data set you might ask Zia for the Revenue Trend. However, the actual column that contains the revenue information could be named Amount. By defining synonyms, you tell Zia that the Amount column is the same as the Revenue data you want. Zia will use this information to get the data from the column Amount whenever you ask for the Revenue.
Revenue by months in 2019
Every time you ask a question, Zia picks the relevant data columns to generate the reports based on intelligently set priorities. Let’s say you have several tables and multiple columns with similar names or types in your workspace. Zia will use the value in the Column Priority option to rank the columns to answer your question.
You can set the priority from high to low and Zia will choose the most appropriate columns to use in the chart based on their priority.
For example, there will be multiple date columns available in a sales data set. If you want to see your monthly revenue, the Closing Date column is the most appropriate one to choose from. But, there’s a chance Zia will pick the wrong date column. In these cases, you can set the highest priority to the Closing Date column, letting Zia know that it’s the right column to be used.
Once you set the highest priority, Zia will automatically fetch the Closing Date column when a relevant question is asked.
Did you know that Zia can also process mathematical functions?
When a question is asked, Zia picks the relevant metrics columns and applies the most appropriate summary function to derive the metric required.
Zia can compute answers to your questions using a wide range of summary functions, such as Sum, Count, Average, Min, and Max to calculate data in your report. Ask Zia also has the option to set a default function to be used for a particular column.
For example, when you ask Zia to show the deal size, Zia will automatically calculate the sum of deals across the month as the answer. However, in this case, the average might be a more relevant function. That’s where the Default Function comes in handy. Using this option, you can set the most appropriate function for a column.
Alternatively, you can specify this function in your question explicitly.
Show me the average deal size by months
In the same way, you can also define and customize these settings at the table level. This will help Zia relate tables and columns more easily.
Over time, Zia will learn your data model and business. As you start using it more, Zia will even understand your data from various domains, relate it, and be able to build powerful reports and KPIs in minutes for you. Not just that – Zia can come up with contextual suggestions and automatically rank data based on your set customization.
With Zia, all you need to do is ask and your data will do the talking for you!
So what are you waiting for?
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