As businesses compete for customers in the digital world, the ability to make quick decisions based on reliable data is vital. Organizations are eager to leverage new technologies like AI, ML, IoT, and the cloud to revolutionize operations and to keep up with competitors.
These modern business practices produce incredibly large amounts of data, and that’s where streaming analytics comes in. They enable organizations to ingest, collect, and analyze real-time and historical data at speeds of less than a second, enabling greater data-driven intelligence, decision-making, and ultimately greater value. .
The possibilities of streaming analytics have never been so great. In fact, 90% of companies believe they need to stay competitive over the next three years, according to my company’s research. Financial institution that needs to adjust customer portfolio attitudes to constantly changing stock prices, utility company that monitors power grid performance, or e-commerce site that needs to produce a monthly report, accurate data at high speed are hugely challenging.
The huge volumes of data that circulate can be misleading, as analytics reports can present false information that appears to be real and lead to bad business decisions. Rather than periodically processing data for last week’s analysis, businesses need to continually add data to quickly highlight computational issues and reduce the chance for errors.
Despite the obvious value of streaming analytics solutions, building a business case around streaming analytics can be a challenge. Many companies rely on consultants to analyze their decision-making processes, but they may miss the mark. Often times, they don’t fully understand infrastructure costs and end up presenting an inaccurate dashboard that doesn’t point teams in the right direction. It’s hard to secure a new system unless you know how much you’re already spending on data structure and analysis, as well as the issues without data and timely decisions.
Despite the obvious value of streaming analytics solutions, building a business case around streaming analytics can be challenging. Many companies rely on consultants to analyze their decision-making processes, but they can lose track. Often times, they don’t fully understand infrastructure costs. and in the end, they come up with an inaccurate dashboard that doesn’t point teams in the right direction. It’s difficult to secure a new system if you don’t know how much you are already spending on data structure and analysis, as well as data-free problems and timely decisions.
To better understand the business case for streaming analytics, organizations need to answer the following questions:
What are your data management goals?
Ask yourself: What should my infrastructure look like in three years, where should my data be, what decision-making powers do I want to have?
Having a clear picture of the specific business goals you want to achieve through better data processes, such as measurable competitive advantage, larger contextual data, or faster product / service delivery, also helps figure out what to expect from an investment in streaming analytics.
What makes up your data flow?
You could manage petabytes or even zettabytes of data. Designing your data flow from start to finish will help you understand where that data is, what format it is in, and what applications are using it. From there, taking stock of the components and data structure involved helps illustrate the current costs of your data environment to better understand potential cost savings.
Who’s going to implement streaming analytics?
Implementing new technology can be a daunting task for IT teams already under pressure. You need to estimate how many people it will take to implement a broadcast analytics platform (and then multiply that estimate by two). Keep in mind that incorporating broadcast analytics can help attract new talent as many developers look for a training opportunity and a place to study ins and outs.
By developing a clear business case for streaming analytics, IT teams can gain the in-house involvement they need to revolutionize their processes with streaming analytics. As a result, companies benefit from strong verifiability with the ability to justify where the numbers come from. also experience higher business speed and invest data processing savings in innovative new areas.
Most importantly, companies can make decisions with confidence knowing that all of their data is current and accurate. Because of this, 57% of real-time data leaders believe they need real-time intelligence to withstand competitive pressures, according to my company’s study cited above. It’s more than just jumping on the latest and greatest in technology – it’s critical to decision-making.
