It used to be that trawling through huge amounts of complex JSON data was the territory of very specialized Data Integration Engineers — or corporate giants that had the time and money to hire teams of engineers. But in today’s world of SaaS applications, Web and Mobile APIs, and IoT devices, almost everyone needs to be able to perform analytics on complex JSON easily. But don’t worry — SlamData has got you covered.
Your data might be coming from Amazon S3, Google Cloud, Azure, or anywhere else. It might be in XML, CSV, or JSON format. We don’t mind. We’ll help you browse your data — even your messy, nested data — just like you’re browsing a file folder.
Think you need a professional data engineer to get anything useful out of your data? Think again. Our software is so user-friendly that anyone — marketers, analysts, engineers, and c-suite execs — can get the info they need, quickly and easily.
Once you’ve found the data you want, just transform it in an analytics-ready table. We’ll take it from there, automatically exporting your clean data to the warehouse of your choice — Amazon Redshift, Teradata, Snowflake, you name it. What you do with it from there is up to you.
It’s no secret that gaming is big — but you might not realize how big. In the US, the gaming industry is over twice the size of the movie industry, and it’s not showing signs of slowing down. All that popularity means huge amounts of data that needs to be parsed, processed, and analyzed.
If you’re in the gaming space, you need to know how people are using your product. That means play time, quitting point, device used, in-game purchases, and a hundred other data points. If your game is online, you’ll want to track interactions between players, playing style, peak server times, ping/lag times, international connections, and more. It sounds overwhelming, but it’s not — not with SlamData on your side.
As populations rise, life expectancy grows, and health care costs continue to increase, the need to treat patients accurately, quickly, and effectively grows with them. AI applications are already using complex algorithms to read medical scans more accurately than human doctors, but there’s a huge amount of logistical work that needs improvement, too.
Properly applied analytics can find patterns in admission rates to predict future trends, keep extremely detailed digital records, trigger warnings and reminders for certain tests, track prescriptions, and find correlations between seemingly unrelated conditions that just might save lives.
There are something like 15 million college students enrolled across the US — together with K-12, the number is more like 75 million. Obviously, we can’t design a custom educational program for each of them — or can we? Educational programs at every level are increasingly digital, and when there’s digitization, there’s data.
Advanced analytics of hundreds of thousands of data points can completely transform the education sector, individualizing curricula, blending online and offline learning, reducing dropouts, and increasing the effectiveness of education for students across the board.
The world of finance is far more complicated than any one person could understand. Billions of data points are generated every day, from credit card transactions to loan calculations to currency trading to the wild world of the stock market.
Finance companies are constantly trying to navigate increased competition, regulatory constraints, and consumer needs to leverage technology and increase efficiency, and a big part of that is the ability to analyze data to predict trends. Collecting and organizing data from the financial sector is a herculean task, but with SlamData, you’re up to it.
Target led the charge on data collection, tracking and correlating its customers behaviors for years before the term “Big Data” even arrived. Now, everyone else is catching up. Traditional retail stores track what customers buy together, what they buy at certain times of day or year, what they buy with a credit card or cash, and so on.
When it comes to online retail, the amount of data generated goes up astronomically. What customers look at before purchasing and for how long, how long it sits in their cart, how often they look at a page before they buy, whether they read reviews or ratings, whether they look at photos, and so on and so on. All of these factors make for useful information to retailers — if they can use the data.
The insurance industry works on the principle of risk. How likely is the customer to file a claim, and how much will it cost when they do? In order to determine premiums, insurance companies need to weigh an ever-increasing array of factors, from basic info like age and type of car to advanced options like telemetry tracking, health data, and genetic information.
Insurance is a trillion-dollar industry, and insurance companies are constantly trying to get an edge with more and more individualized assessments, policies, and premiums. Collection and analysis of data is how they do that.
Huge amounts of complex data used to be the territory of a few specific tech industries — not anymore. No matter what industry you’re in, you’re probably collecting more data than you know what to do with, from behavior to usage to demographics. Turning that data into actionable conclusions is where we come in. With SlamData, you can import data in any form from any source and transform it into tables ready for analysis in seconds.