InetSof Webinar: Search in a Data Discovery Solution

This is the continuation of the transcript of a Webinar hosted by InetSoft on the topic of "Why You Need Data Discovery Software." The speaker is Abhishek Gupta, Product Manager at InetSoft.

Some people are curious how to integrate SQL and search in a data discovery solution. The way we serve SQL in search is we actually have SQL extensions that allow you to perform the full text search operations, and you can construct in a SQL query that could join relevant information together, such as perform aggregation. Then when you get to the actual where statement for doing the filtering of what information is there, you can provide a much more flexible filter parameter.

That’s basically a keyword search that can look across all the data that’s involved in the query and look across all the fields. It’s a very flexible ad hoc way of refining and adjusting search and adjusting the SQL query. You can also use those operators as a table function so use keyword search to select the set of data to work with rather than just being restricted to just tables. So it’s a whole new mechanism for pulling sets of data, still using SQL as a mechanism for joining and aggregating and analyzing information.

Being able to analyze unified information for the ordinary business user in a way that they can get it themselves, I can’t tell you how many times in my career I’ve had data and the data warehouse, and then I’ve got a file over here that some vendor sent me, and I’ve been frustrated by trying to bring those two things together. I don’t have time for some ETL project or some difficult way or some programmatic way with APIs to mash that stuff together.

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So, of course I would jam it into excel and do crazy look up functions to join them. And I think the idea that people can mash up information themselves, when they know it’s the right context information that they need is a really important thing. Blending data or mashing up information is really critical for being able to use one source of information to filter and find insights.

With our data mashup solution, the interface handles your SQL querying so you don’t have to be SQL expert. But we work though the SQL so that yes you can blend across data sources. You can query one data source and another data source, whatever that other source is. It could be structured information or unstructured information.

I think people are becoming increasingly sophisticated about the need to bring information together, and they need it now. So the ability to provide the user with the capability to bring data together I think is an important thing that data mashup can serve. We see a lot of our customers demanding it for their corporate dashboards.

We have a customer who runs a hospital system in very fast growing area, and they just can’t keep up with the change in their end user community. The end users are constantly changing their needs. In this particular community it’s housing starts that they need to analyze. They need to be able to bring in different kinds of data to know what’s going on in their markets to answer those questions, and that’s a really important function for them. So I think data discovery and unified information access is critical to that, with ease of use for the average user being really critical, too.

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One of the most important things is that the process is repeatable so that you can take this with new analysis and update it in the future. The process that you endeavor to drive in analytics is repeatable so that you can easily adapt it. You can change it to fit whatever conditions present themselves. And it’s done by the business owner. It’s that line of business user that’s the one that actually interacting with the information.

What would be the performance impact be if we allow unstructured information through the same interface that has structured data sources? It depends on the type of infrastructure you’re using for Unified Information Access so. For example, our infrastructure really is optimized so that you actually get a huge amount of compression on that unstructured information when you bring it into the system.

So that’s something that we view obviously as very important. Once you bring it in though again it’s all process down to the same fundamental levels of information. So from a query perspective, there really is no substantial difference between whether the information you’re hitting happens to originally come from SharePoint, for example, or if it happens to come from a CRM System.

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