Real-time data processing in the cloud is a trend that is impacting organizations for the better, and Amazon Kinesis is a great tool to help your business leverage real-time data.
Data is the lifeblood of any modern company.
Whether it’s customer data to analyze purchase behavior, location data to determine geographical trends, or social media data to assess brand sentiment, data is crucial in growing your business.
Even more powerful than data is real-time data.
If you can capture and analyze real-time data about your customers, processes, or competitors, you have the ability to react quickly to important events.
There many issues with working with data and extracting insights from it. Here are a few to start:
- Many times there is so much data that it’s difficult to work with, and there are many questions that come with large amounts of data. Where do you store it? How often and quickly will you need to access it? How will you manage it all?
- Data may be siloed within different departments, and bringing it all together is a big pain.
- Real-time data can’t be analyzed fast enough to make timely decisions.
Cloud computing has made many strides in allowing organizations to capture, process, and extract insights from real-time data. Cloud providers have built tools that let companies be more agile and immediately take advantage of trends and events.
By moving your data processing to the cloud, you don’t have to worry about having the storage capacity to hold all of this data nor the server capacity to process it. The cloud will also allow you to analyze this data more quickly and seamlessly.
Amazon Kinesis is a data processing cloud tool that we really like.
Overview of data processing in the cloud with Amazon Kinesis
Amazon Kinesis is a suite of tools from Amazon Web Services that makes it easy for companies to work with high volumes of real-time streaming data.
Kinesis has three components:
- Kinesis Firehose, which allows you to easily load streaming data to other AWS components such as S3 (Simple Storage Service), Redshift (data warehouse), or Elasticsearch Service
- Kinesis Streams, which you can use to build custom applications that process and analyze real-time streaming data for specialized needs
- Kinesis Analytics, which lets you easily run SQL queries on streaming data
Kinesis’ tools allow you to process data in near-real time, the throughput of data streams can be dynamically adjusted, and like other AWS services, there are no upfront or setup costs involved.
Applications of Data Processing in the Cloud
There are many different scenarios where Kinesis can be applied to process data.
One prime example for using Amazon Kinesis is location data collection at events, a project that we’ve recently worked on.
The tracking of attendees’ movements throughout an event site is extremely valuable for both event planners and sponsors.
Event planners can collect attendee location data via beacons to better understand how they travel throughout the event site. When this data is analyzed in real time, event planners can react quickly to reroute attendees and change layouts to avoid bottlenecks.
This data is also extremely valuable for sponsors who purchase booth space at the event.
Sponsors want attendees to come by their booth so they can engage them with information about their products and services. A thorough understanding of how many attendees walked by, at what times, and how long they dwelled in certain areas will help sponsors assign staff to optimal locations, calculate ROI, and plan for future event sponsorships.
A lot of data can be collected at events, which makes this a perfect scenario for Amazon Kinesis Firehose.
You can capture all of the location data via beacons and send it to Kinesis Firehose. Firehose will then continually load the data directly into Amazon S3, Redshift, and Elasticsearch Service so you can analyze and provide insight proactively and in near real-time. You can then provide reports to your event planners and sponsors so they can act accordingly.
Amazon Kinesis Firehose. Image courtesy of Amazon.
An e-commerce website can also use Amazon Kinesis to capture and analyze visitors’ views, clicks, and purchase behaviors and provide customer insight. Depending on the type of analysis that is necessary, Amazon Kinesis Streams allows you to build custom applications to collect, process, and analyze huge amounts of customer data for any particular situation.
For instance, if you run an online women’s clothing store, you can use Amazon Kinesis Streams to build a recommendation engine that serves up product suggestions that are similar to what has been viewed by your website visitors. The behavior data that you collect minute-by-minute can help your recommendation algorithm get smarter and display product offerings that more accurately match what users want.
These kinds of analyses can lead to optimized conversion rates, sales growth, and increased customer satisfaction.
In any scenario, Amazon Kinesis Analytics makes it super easy to analyze all of this streaming data that you collect for your business.
Let’s say that you run a manufacturing business. There are many moving parts to your company and associated data, such as customer info, machine uptime statistics, shipping data, and much more. And it’s likely that all of this info are in disparate systems and are hard to analyze and extract insights from.
So you can use Kinesis Firehose or Streams to capture and process all of this data and then leverage Kinesis Analytics to run standard SQL queries against these data streams.
Then you can even send this data to other analytics and monitoring tools to create alerts for when machines go down, a new customer has been acquired, or when a shipment goes out the door.
As you can see, Amazon Kinesis has a powerful and customizable suite of tools that can help you leverage real-time data to garner insights and improve your business’ bottom line.
Data is so important for any organization, but many companies can’t take full advantage of their data.
Often, this is because there is so much data being generated that it’s extremely difficult to harness, process, and analyze all of it.
This problem is compounded with real-time streaming data.
But cloud computing has made it much easier to leverage data, especially real-time data, to make faster, more informed decisions. This will help you better serve your customers, ensure uptime of your equipment, run more effective ad campaigns, and improve your business.
What are your thoughts on data processing in the cloud? Are you leveraging the cloud for data processing at your company? We’d love to hear from you in the comments.
Like this post? Please share it using the share buttons to the left! Then join our mailing list below and follow us on Twitter – @thorntech – for future updates.