Most companies are either good with scraping data or working with data. IMS excels in both. We can scrape large amounts of data and take action on it to make it much more useful for our customers. This includes normalizing, cleaning, segmenting, analyzing, and visualizing data. This allows our customers to easily integrate data into their BI and CRM systems and much more.Request Demo
We manage thousands of IP addresses and most of our scraping tools are virtually undetectable. Because of that fact alone, we don't look like a spider or a scraper when collecting the data. This is huge advantage makes it a lot easier for us to pivot or adapt in the rare occasions that we get deferred or slowed down.
Our core team of scraper engineers have been working together for over 16 years. These guys are best-in-class. They really know their stuff. They keep up with the latest and greatest scraping technology. They can get behind the really complex sites (e.g. with CAPTCHA) that a lot of companies can't.
One of the big challenges of collecting or scrapping data is that you now have to make heads or tails out of it. It's all in a big bucket, so to speak, and you've got to look at every single field of data and understand how you could use that data to give you actionable insights. And insights don't just pop off the page. Data Analysis is what turns scraped data (information) into useful data (knowledge).
We started as a data analysis company almost 40 years ago, and now it is second nature to us. Being able to deal with large volumes of data allows us to provide data in the exact way that a customer wants to see it. We ensure that data is accurate, delivered in a timely manner and supported by our technical and customer service personnel.
We have REAL people representing the company, representing the data, and representing the process. As a customer you are able to interact with our trained stuff (all the way to IT if needed) and get supported every step of the way. We are here to answer questions about data, not hide behind it.
For some companies working with big data can be quite awkward, almost bring the entire operations to a crawl. It's very difficult just to take a lot of data, throw it into a database, and keep your fingers crossed hoping it's going to work.
Working with big data requires that you prepare it in a way that you could consume it later. There's a lot of work that you need to do in advance to normalize, cleanse, and segmenting the data.
We deal with big data daily. We have a culture and a discipline throughout our operations that support working and managing vast amounts of data. We closely watch and understand how data changes, so no insight is missed, no data lost and our systems operate at top efficiency.
We are also a highly innovative tech company. For the past 18 years, we have been recognized by the Canadian Revenue Agency with numerous grants that continue to support our technology advancements in the data space.
Many of our customers get their data delivered into a dashboard system or series of reports that we build for them. It's pre-canned and you can't go wrong with it. You log in, select what you're looking for, and the data that you want instantly appears on the page in front of you. It allows users to get in, get access to the data quickly, and get out.Request Demo
Some customers choose to get their data in a feed. It's the raw data that is delivered to the customer on a scheduled basis. Many of our customers use this approach to manipulate the data inside their own BI (Business Intelligence) or CRM tools.Request Demo
One of the coolest ways we can deliver data is Tableau. It's extremely flexible, it's fast and it looks amazing. Tableau can take any data we collect in near real time and allow the user to run analytics or understand that data in a visual form. Not only can you do the same type of 'rows-and-columns' reports you see in Excel, but you can visualize data in a whole different way: with graphs, charts, heat maps, geo maps and much more. This makes it more appealing and powerful than looking at a series of rows and columns.Request Demo