Developers are at the forefront of analytics innovation, driving an evolution in analytics beyond traditional BI and reporting to modern analytics applications. These applications—fueled by the digitization of businesses—are being built for real-time observability at scale for cloud products and services, next-gen operational visibility for security and IT, revenue-impacting insights and recommendations, and for extending analytics to external customers . And Apache Druid has been the database of choice for analytics applications trusted by developers of 1000+ companies, including Netflix, Confluent, and Salesforce.
We are at the forefront of an analytics evolution, moving beyond traditional BI and reporting to modern analytics applications.
Virtually every company is becoming a software company at this point in tech. Now that everyone has easy access to the cloud simply building cloud software and services isn’t enough to keep an edge on competitors. However, there’s a changing of the guards happening in terms of who is creating value from data within an organization, and the impact will be felt predominantly in the apps industry.
Companies like Netflix, Twitter, and AirBnB are creating modern analytics applications that are challenging the way we traditionally think about data application and business intelligence—optimizing how they build their products, how they share information with customers, and how they inform advertisers, shareholders and more.
Consider the traditional narrative around the use of analytics. BI experts would pull historical data into a query for earnings reports, executive dashboards, or projections for the next quarter, but it’s now time to let the genie out of the bottle. Analytics apps can do so much more with the data that’s already circulating around us.
Creating an analytics-based app is most effectively accomplished using two tools: a powerful database and a savvy software developer. By placing more data in the hands of developers, companies have the opportunity to take analytics to the next level, enabling data that already exists to be much more impactful and real-time.
What to Expect
Modern analytics applications deliver an interactive data experience for investigative, operational, and customer-facing insights. They help businesses to make the best data-informed decisions and create the best product experiences for their customers.
Whether it’s next-gen observability, user behavior insights, live A/B testing, or even recommendation engines, an analytics app won’t disappoint.
There are many valuable use cases of analytics apps already in play today. AirBnB has optimized its business model by developing an app that collects, organizes, and processes mass amounts of data to inform decision-making across various parts of its organization. The Twitter MoPub app, which was acquired by AppLovin in October, is a mobile ad network that helps mobile publishers manage their ad inventory through the use of deep analytics and insights. Lastly, Netflix is creating a huge competitive advantage by bringing together Apache Kafka and Apache Druid to build an analytics app that enables a high-quality, always-on user experience.
The Developer’s Seat
The software developer is the knight in shining armor to make it all happen. The reason the software developer is so critical to analytics-based apps is that they’re the ones that understand—and thus can ensure—the scalability, concurrency, and security needed to do it right. They also have their hands on high-performance real-time analytics databases like Apache Druid and can capitalize on all of those capabilities to deliver an app that is interactive and intuitive for the end user.
A popular choice among developers is Apache Druid because it’s designed for workflows that depend on fast queries and excels at instant data visibility, ad-hoc queries, operational analytics, and handling high concurrency. With this powerful tool, developers can improve:
- Scalability: Interactive analytics at scale is going to be a huge area of focus for companies moving forward. Analytics apps provide so much value because they allow the user to investigate and interact with any data set they want in real-time and at any scale. Alas, only a developer-built application will be capable of providing such a dynamic user experience.
- Concurrency: Considering every data-driven company is eager to give everyone access to explore its data, the issue of concurrency is critical. It goes beyond just user count, rather than developing an app that can handle dozens of visualizations, with each firing off several concurrent SQL queries. Again, a powerful database is critical here.
- Streaming: Continuous, real-time insights are the foundation on which a modern analytics app is built. There is so much that can be done with streaming data, but without the aid of the software developer, many companies aren’t able to keep pace. With an eye on real-time analytics, several things have to be taken into account: Is analyzing streams alone enough, or does the use case need to compare streams against historical data? Does ingestion scalability matter, or does it require processing millions of events per second? What about latency or data quality?
Benefits to the Customer
While analytics must still deliver value to the business, more and more companies want to deliver these insights to their customers, too. This is opening up new levels of operational visibility, superior product experiences, and value for customers that simply hasn’t been seen before. Companies like Twitter, Cisco ThousandEyes, and Citrix are driving material revenue with Apache Druid and Imply. They’re giving their customers visibility and insights, which is creating big business for them in return.
Not just any database can be used to build a customer-facing analytics app. There’s way more on the line than internal use cases when we think about service-level agreements and the customer experience. Even microseconds of latency make a difference when it comes to customer satisfaction. That’s why it’s important to utilize a database that has high concurrency and real-time analytics in its DNA.
The days of static reports and dashboards are in the rear-view mirror, and the successor is an analytics application that can rapidly explore and visualize exceptionally large units of raw, high cardinality data in a matter of seconds and in a way that is intuitive to the end user. Developers will be at the forefront of this push for more informative, real-time, business-driving solutions that help keep data-driven companies at the forefront.