Mainframe Data Streaming 101: Maximize Mainframe Data and Reduce Complexities With the Next Big Transformation Strategy
Best Practices
Maximizing the data on your mainframe often feels like a Catch-22.
When you access data from your mainframe, you encounter the complexities of legacy languages and older database structures. But reducing complexity requires changes to your mainframe that might compromise mission-critical applications or sensitive data.
Mainframe data streaming helps you bypass this mainframe dilemma. A data streaming strategy creates a pipeline from the mainframe to the cloud, allowing you to use mainframe data in near-real time. As a result, you can take advantage of cloud-based applications and modern analytics platforms — reducing costs and maximizing insights.
Mainframe data streaming is quickly becoming an essential business function as organizations take advantage of new cloud data analytics and AI platforms. But before you stream data, you need to understand where it can go wrong — and how a partner can help.
Why mainframe data streaming may not be as simple as it sounds
Mainframe data streaming reduces mainframe complexity, but it requires planning. Streaming different types of data formats poses a challenge. Formats can vary depending on where the data comes from and the times of day it is received.
For instance, Electronic Point of Sale (EPOS) devices may upload data at the end of the day and process that data in the mainframe as a batch job. On the other hand, IoT devices may send data intermittently. For a successful mainframe data streaming process, you need to take these variables into consideration and ensure your stream can handle a variety of formats.
Mainframe data streaming can also introduce challenges when the original data isn’t managed correctly or if the data is poor quality. If the data is messy, incomplete, or incorrect, it can cause streaming errors. This poor-quality output introduces additional complexities when used with foundational AI models. The bottom line: Proper governance of source data and correct processing is crucial for successful mainframe data streaming off the mainframe.
Unlock the limitless potential of your mainframe data
To take advantage of mainframe data streaming while avoiding these pitfalls, you’ll need a partner who has handled them before.
An expert data provider can offer expertise on processes and protocols that keep data accurate, consistent, secure, and compliant with regulations. By helping you plan for various data formats and ensuring you have an established data management process, a provider enables you to tap into mainframe data streaming possibilities.
Additionally, data providers can shed light on business operating models tied to successful data management. They align data strategies with overall business objectives, identify key performance indicators (KPIs) that are tied to data usage, and suggest ways to optimize processes based on data-driven insights.
By providing process and best practices, a provider uses your mainframe data to unlock the latest cloud innovations. So what does a successful data streaming strategy look like for organizations across industries?
1. Retail
Instead of waiting for inventory updates after nightly batch schedules, retail operations can use mainframe data streaming to access real-time inventory updates from warehouses or stores. As a result, retailers can make quicker decisions on restocking or promotions.
2. Healthcare
Healthcare organizations can stream data in real time from sources across providers. By connecting the dots between patient insights more quickly, they can proactively detect and monitor early signs of disease.
3. Government
Government agencies can use real-time access to mainframe data to improve constituents’ everyday lives. For example, agencies can analyze traffic data to manage public transit schedules and plan infrastructure improvements based on usage patterns.
4. Financial services firms
Financial services firms can improve risk management by streaming portfolio, regulatory, and market data from their mainframe. By analyzing streamed data, firms can assess risk profile and ensure regulatory compliance by monitoring risk exposure in real time.
The possibilities of mainframe data streaming are endless. Regardless of how you use mainframe data streaming, this strategy turns mainframe data into actionable insights faster.
Stream data off your mainframe with Ensono
As you introduce data streaming, you need a partner who can help you successfully create a pipeline between your mainframe and the cloud.
Ensono is uniquely positioned to offer mainframe database services based on our extensive experience managing some of the world’s largest mainframes. As a highly accredited public cloud provider, we also deliver unmatched mainframe to cloud expertise.
Need a partner to help with your mainframe data streaming strategy? Get in touch.