Q&A from “Quantifying the True Value of Collaborative Data Prep” Webinar with Blue Hill Research
Our curious audience sure inspired a lively discussion during our webinar “Quantifying the True Value of Collaborative Data Prep” with James Haight of Blue Hill Research and Andrew Comstock, Director of Product Management for Informatica Data Preparation.
Insights are best when shared. So we thought we’d share the top questions from the audience, along James Haight’s responses.
Miss the live webinar? We’ll get you up to speed! Grab the highlights in our webinar recap “Blue Hill Research Links Dollars to Analysts’ Data Prep Time” or sit back and catch the replay any time!
Q & A Recap
- “I have seen that the “traditional” business intelligence tools are falling out of favor. Too expensive, learning curve can be steep, etc. In favor of data visualization tools that are leaner and easier to learn. Thoughts?”
Andrew Comstock: James, how are self-service and data preparation tools changing the aspects of data visualization? How are they changing those next directions?
James Haight: Old BI tools are definitely falling out of favor. To that, there’s no doubt. Even the traditional players recognize this. Data discovery, visual interfaces, a guided user experience: this is the way of the future…
There’s no doubt that there’s an opportunity for people to better understand and investigate their data with these data visualization platforms that allow for self-service, that let you manipulate your data and explore it without writing a single line of code. That is absolutely the way of the future.
People like Tableau and Qlik pioneered this, and now the big boys are starting to write the ship and invest heavily in this as well. A sea change is coming and is already in progress. That’s the way of the future…
To the second point, how is data preparation—this new breed of solutions—interplaying with data visualization and this new breed of BI solutions?
I think the answer is really simple: it’s increasing accessibility and allowing individuals to do more than they ever could before.
So if you think of the great value prop of these data discovery solutions, now someone who is not a data scientist—they’re just a regular data analyst or business analyst—can pull all this data into their data discovery tool and get answers without having to rely on a centralized IT organization.
They can get things fast. They can be quick and agile and get all these insights they never had before.
But, the flip side is that they’re constrained by what data they can actually bring into it.
Maybe something is great ingesting a couple thousand rows of very clean data, but all of a sudden if you’re trying to extend the accessibility of this to something that needs to analyze hundreds of thousands of machine sensors and social feeds, you need something on that data preparation end that allows you to do that…so whereas this used to be the purview (these challenges of scale and complexity were the purview of the people who write code like data scientists), now all of a sudden, these self-service data prep tools bring that capability in a code-free way, in a guided way, to the same people that are using these next-generation business intelligence solutions as well.
So, now, there’s finally this uniting of both the ingestion of data as well as the explanation of data, the visualization on the front end. It’s finally completing the second half of the puzzle there.
- What are the offerings from Informatica in this space?
(We ran out of time to address this question during the live webinar, so we’ll answer it here!)
Informatica offers a cloud-based data preparation application with a familiar spreadsheet-like environment, designed for business analysts and professionals who want to bring in any data, from multiple data sources, and then prepare, cleanse, blend, and reshape ad hoc datasets for self-service analytics and data visualization.
Want to see how it works? Get started today with a free 30-day trial of Informatica Data Prep.
- Can you please give some examples of daily data prep activities a data analyst performs using, for example, Excel?
James provided common examples from sales and marketing. Let’s say you have 15 different prospect databases and you’re looking at emails and zip codes, you need to parse them and repair numbers that were left out, or standardize state codes and cities.
He also explained a more complex example when a data analyst needs to align machine sensors with 60 readings an hour with sales data created once a day.
Get all the details by watching the on-demand webinar.
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