Real-Time Data Streaming 101: What It Is & Why It’s Important
Introduction to Real-Time Data Streaming
Any data that is moving from one location to another is by definition part of a data stream. If that movement is happening when the data is created you could call it real-time data streaming. From carrier pigeon to high-frequency trading, or paperboy on a bike to alerts on your phone, the objective has always been to deliver data effectively and efficiently. Optimizing the various variables has always the objective. Improving the delivery method, increasing the speed and ensuring the data quality is something that each new method works to improve. The ideal is to be capable and reactive when data events occur, as they occur.
Any data that is moving from one location to another is by definition part of a data stream.
As you read this very article, metrics are being delivered — how you got here, how long you stay, whether you continue with your (hopefully favorable!) journey, and so forth — ready to be compiled and evaluated in real time.
An easy way to envision the power of real-time data is to think of the rise of ride-hailing companies (and the valuations attached to them). Apps designed to connect us, our location, and available drivers must process streaming data efficiently. These ride-hailing apps gather your location as well as dozens (or hundreds) of drivers all in real-time. Matching available drivers near your location, along with other requirements you may have entered, so fast that the complexity of the application is completely hidden from the users. Users see maps with cars headed to them in real-time. As users of the service, we expect as much, and would find the previous tech in this sector — the pre-automation decades of calling a dispatcher at a taxi service — inconvenient and unacceptable now that a better model has achieved ubiquity. This better model is the new normal. The new normal will no doubt be improved upon with a future disruptive technology that comes up with a better offer.
In today’s hyper-competitive, data-saturated world, business professionals must utilize the right tools to optimize continuous, real-time data integration; failure to do so may result in forfeiting opportunities that require transactional decisions based on the availability of actionable analytics. Real-time data streaming should be considered essential for real-time BI, and vital for those businesses seeking the ever-elusive edge over the competition. (In other words, everyone.)
Benefits of Real-Time Data Streaming
Like the ride-hailing companies, examples of how the explosion of streaming data has the ability to foster growth in business are everywhere. Here are just a few:
- Streaming music now comprises almost half of all annual music revenue, with paid streaming services up 33% from 2017 to 2018.
- PayPal’s fraud prevention prides itself on staying “one step ahead of the bad guys.” They’re responsible for dozens of petabytes of data, and keep customer data secure through real-time analysis (within milliseconds) of each transaction to identify potential fraud.
- Lufthansa Systems, a division of Lufthansa Airlines, provides real-time data analytics to more than one-third of all the world’s airlines. Flight route optimization generates millions in profits for their clients, and is only possible by utilizing real-time data streams.
This increase in data speed, data volumes, integration, and application are both drivers in, and representations of, more efficient levels of production. In the business world, who doesn’t desire (or demand) higher productivity rates? That question answers itself; the more relevant question, in today’s IoT world, is, “who can afford to not stay plugged into optimized data streams, and operate their BI tools at the speed of insight?” Again, same answer — business leaders do not have the luxury of “good enough” when it comes to extracting value from source data. The objective is finding the fastest way to get data where you need it, while ensuring that data feeds are clean, faithful, and the proper integration and analysis tools are implemented to render maximum ROI.
It’s All About Speed to Insight
At HVR, we’ve built our platform around just that: getting your data where you need it. We provide you with control over your data as it travels between databases, warehouses, and the cloud, keeping it secure and scaling as your company grows. We’ve architected our solution to be focused on real-time, continuous data integration, always validating, and constantly seeking efficiencies that improve performance.
Our aim is to best assist optimizing your data pipeline from on-premise to the cloud and back, and this attention to detail also means providing guidance while giving you control over how data should best be processed in order to achieve stated objectives. For example, there are times when batch processing of data might be desired due to the sheer bulk of incoming data coupled with maximizing efficiencies (some data — supply chain records to be archived, or monthly sales reports — may be best suited for processing in bulk, thereby simultaneously prioritizing the data necessary to process in real-time in order to derive business insight).
Here is a straightforward way to remember the value of actionable analytics via stream processing: Real-time data streaming should work hand-in-glove with real-world decision making. Choosing an effective data integration solution makes it all possible, and that’s what we do at HVR. Our GUI is a simple download away; with it, you’ll have an all-in-one solution that puts you in the driver’s seat, in full control of all your data’s potential.