David Wang, Vice President of Product Marketing at Imply, shares his 2022 predictions of the rise of a new analytics hero.
Every year industry pundits predict data and analytics become more valuable the following year. However, this does not take a crystal ball to predict. There is something much more interesting happening that will change everything in the analytics world: the rise of a new hero, the software developer.
If the past indicates the future, then what we are seeing is a major transformation unfolding across every industry. A changing of the guard, so to speak, of the ones who are creating value from data.”
Today, the industry equates analytics with data warehousing and business intelligence. It is a traditional approach of BI experts querying historical data “once in a while” for the executive dashboards and reports that have been around for decades.
For bleeding-edge companies like Netflix, Target, and Salesforce, their use of analytics is much more progressive – and much more impactful and real-time. Companies like these see the true game-changer for data in the hands of their software developers. These developers build modern analytics applications with Apache Druid to deliver interactive data experiences for investigative, operational, and customer-facing insights.
What is causing the emergence of these apps, and what does it mean for developers? Wang has broken down the top five reasons:
#1 The need for interactive analytics at scale is taking off
Increasingly, analytics are needed to understand a situation or investigate a problem. This requires the freedom to slice and dice and interact with data live with sub-second query response at any scale. It is a dynamic user experience that can be created via a developer-built application.
No one wants to sit around waiting for a query to process, and while many databases will claim the checkbox for interactivity and speed, they will come with many scale constraints. They will rely on tricks like roll ups, aggregations, or recent data only to make queries appear faster, but that restricts the insights that can be generated.
#2 High concurrency is becoming a must-have for every use case
The days of relying on a few business intelligence (BI) analysts to write SQL queries are seemingly in the rear-view. Today’s data-driven companies want to give everyone free access to explore, from product managers to ops teams to data scientists, and multi-tenancy takes user count even further. However, concurrency doesn’t just come from the number of users. Developers are being asked to build analytics apps with dozens of visualizations, each firing off several concurrent SQL queries.
It will be hard to find a modern database today that doesn’t claim high concurrency. Users obviously wouldn’t want to force fit Postgres (or even Elastic) in uncomfortable positions. However, what about scale-out cloud data warehouses? Doesn’t elasticity = scale = high concurrency? Of course, elasticity without insane compute efficiency (like with Apache Druid) will result in a really expensive app.
#3 Desire to unlock the value of streaming data with analytics
Businesses of all kinds are rapidly adopting event-streaming platforms like Apache Kafka. Confluent, the creators of Kafka, have built a data mesh that puts data ‘in motion’. With data swirling around constantly, what better use of it than to analyze it for continuous, real-time insights?
Companies like Netflix are doing this with its developers creating a huge competitive advantage by bringing together Apache Kafka and Druid to build an analytics app that enables high quality, always-on user experience.
With an eye on real-time analytics, several things have to be considered. Is analyzing streams alone enough – or does the use case need to compare streams against historical data? For intercontinental exchange, the full spectrum from present to past gives them the right security visibility. Does ingestion scalability matter – do you need to process millions of events per second? What about latency or data quality?
#4 More and more companies want to give their customers analytics
Analytics of the past were about making better decisions for the business. While still very relevant – and a huge opportunity to create more value – we increasingly see companies build analytics apps to deliver insights to their customers.
Companies like Twitter, Cisco ThousandEyes, and Citrix are doing this and driving material revenue. In addition, these companies are giving their customers visibility and insights, which creates big business for them.
But it can be a pretty hairy outcome to use any database to build a customer-facing analytics app. There is way more on the line than internal use cases when you think about SLAs and the customer experience. In these apps, microseconds of latency make a difference, downtime is costly, and concurrency and $$ goes through the roof. Thankfully there’s a database for that!
#5 The digitization of everything is built with analytics
At this point in tech, Wang thinks every company is becoming a software company. However, with everyone having easy access to the cloud, simply building cloud software and services isn’t enough to sustain an advantage. That is why companies like Salesforce and AirBnB build analytics apps to optimize how they develop their products.
At the best software companies, developers are building analytics apps to help them create the best product experiences. Whether it is next-gen observability, user behavior insights, live A/B testing, or even recommendation engines, an analytics app is at work.
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The crystal ball for 2022
There you have it. Imply’s predictions for 2022. The world of analytics is expanding rapidly to modern analytics apps – with developers becoming the new analytics heroes in organizations.