One of the biggest challenges organizations face today is ensuring that many different types of users get analytics access to granular data in a timely manner. Gone are the days when day-old, aggregated data was sufficient for making critical business decisions. The need for immediate access to data is a popular theme in business today, and the most successful companies will be the ones that can react quickly to their changing environments.
This is the reason why the notion of agile BI is becoming top of mind. Agile BI is about letting data consumers analyze all levels of data without the typical delays found in a traditional environment. Users don’t want to, or can’t, endure delays due to slow processes or technology limitations. They also don’t want to have to spell out exactly what they need up front prior to getting access to the data. They want the flexibility to explore a variety of data sets, including ones they did not anticipate they needed, to get the insights to let them be successful in their job.
A key enabler of agile BI is the availability of interactive, self-service analytical capabilities on enterprise-wide data. End users should be able to ask any query on the data without continually turning to IT for changes to the data sets. But agile BI is not only about what users can do once they have data access. It is also about how quickly users can get to all the data. In the past, “self-service” was a misnomer in that business analysts only attained freedom in bursts. While they enjoyed self-service once they were given access to data, the route to that point was far from fast. IT teams were spending hours, days, and even weeks behind the scenes to prepare data for use by analysts. The problem today gets worse as companies generate more and more data. The data management effort grows as the data grows, but companies often don’t increase headcount to keep up with the greater IT requirements. This means that IT teams are further burdened by big data challenges which result in significant delays for business users.
Traditional BI tools simply can’t deliver the modern expectations around agility. These tools can’t provide BI for all types of users and typically require significant IT intervention to make data ready for analysis. This is largely due to the scale limitations, thus forcing the use of extracts that only summarize data. Whenever details are needed, more data modeling and movement is required. Typically, if end users need new analytics reports, they’ll need to request changes to the data from their swamped IT department, thus waiting days or sometimes weeks to run their analytics. Users also find it difficult to collaborate using these traditional BI solutions. With the limited data found in extracts, there is less opportunity for exploratory collaboration that leads to new insights. Their interactions typically are limited to email, phone, or chat without the benefit of visually based data sharing.
If you expect business agility in your BI practices, plan ahead for an architecture using an agile BI platform that can provide:
- Minimal data movement. In traditional BI environments, analysts could only ask new types of questions once the IT team prepared the data for them. This entailed moving data to another repository with intensive data transformations, which added significant delays and risk of error. If instead, your BI platform did not need significant up-front modeling that limited the types of queries you could run, then you could reduce IT dependencies and thus speed up the time-to-insight.
- Direct access to granular data. Related to the above, users have historically been given an extracted summary of data sets rather than the entire data set. This was done to boost query speeds on specific types/sets of queries. The problem is that if users needed to drill down into details or run different types of queries, they would have to send a new request to the IT team. If you can avoid the extraction steps and otherwise boost performance on the direct access to granular data, users can run analysis on aggregated data as well as on the underlying detailed data.
- Scalability. As more data and users are brought into the system, the ability to handle that new load is critical. Modern BI platforms need to be able to scale in an efficient way. With the massive increases in data volumes these days, this scaling ability requires a scale-out architecture on commodity hardware, especially when cost-effectiveness is a factor.
- Collaboration. Oftentimes, business analysts run their analytics on a standalone desktop tool like Excel, which makes collaboration and sharing more difficult. Instead, browser-based applications built on your BI platform enable interaction and ongoing insights among your user community. The ability to build and deploy analytical applications on your BI platform is an important capability for finding insights as a team.
As mentioned earlier, traditional BI technologies are not well suited for modern environments requiring faster analytic access to detailed data. That’s why a host of new technologies are emerging as faster, more scalable, and more flexible options to the traditional technologies.
The Data-Native Architecture
One increasingly popular technology for big data analytics today leverages what’s known as a “data-native architecture.” Data-native refers to the use of analytics and data-centric applications that run where the data resides, without data movement. This means that if you have data stored in a data platform like Hadoop or cloud instances, you use those compute resources to analyze your data. The beauty of a data-native architecture is that it puts end users in direct contact with the data they need. Instead of external applications that need to pull the necessary data from their data sources with IT intervention, data-native applications sit within the data source to accelerate performance and reduce system complexity.
Your data-native BI platform should include the following features:
- An easy-to-use visual interface. Your agile BI platform should include an easy-to-use visual interface that lets you do exploration/semantic modeling directly on all your data. You should be able to assemble dashboards and applications of visuals that show your work, with interactive drill down to raw data, so you can zoom and pivot with seamless precision to any values in your data sets.
- Browser-based. Your BI platform needs to be browser-based so it can enable collaboration across teams, across locations, and across devices, while enabling self-service drag-and-drop authoring to create a full range of charts and graphs. You should be able to easily create, embed, and publish visualizations with secure access to fine-grained data, for any user with a modern browser.
How Does Arcadia Enterprise Address These Issues?
Arcadia Enterprise, the flagship product from Arcadia Data, is built on a data-native architecture that solves many of the challenges businesses face today when analyzing big data. Arcadia Enterprise gives you a truly interactive and self-service environment to fulfill your requirements around agile BI. It runs directly in your big data platform, so not only do you reduce the delay in moving data to a separate, dedicated BI platform, but you also reduce the complexity and thus the chance for error. In addition, since you are accessing the data where it resides, you have access to all of our original data details. This allows you to immediately drill down into details to get hidden insights you would not get from higher level queries on summarized/aggregated data. The architecture also allows horizontal scaling, like most true big data platforms, so as your big data cluster grows, Arcadia Enterprise can scale along.
Other technologies theoretically offer a similar architecture, but fall short in terms of performance, latency, and concurrency. Arcadia Enterprise offers a query optimization capability using what we refer to as “analytical views.” Analytical views are precomputed and cached data sets that speed up results drastically for dashboards and analytical applications in Arcadia Enterprise. This allows quick responses for queries over billions of records from thousands of concurrent users.
Analytical views can be created at any time in the cluster to accelerate queries. No time-consuming data modeling, no query rewriting, and no application refactoring are required. Arcadia Enterprise also provides Smart Acceleration™, which is a recommendation engine that suggests new analytical views based on query patterns and statistics, to accelerate the range of queries that users run. This makes the setup of a complete analytical environment far more streamlined than what is available with other technologies.
Another advantage of Arcadia Enterprise is how it enables collaboration. Building applications using a wide variety of visuals can be done in the interface by any user. This lets you operationalize your analytical dashboards for use among a larger user base. Since the dashboards run in a browser using HTML5, you get rich experiences without having to install a desktop BI tool for anyone needing to access the data. You can even easily access your dashboards on your mobile devices in a clean, mobile-friendly output.
Arcadia Enterprise provides the following features that enable true agility, bringing business-driven visual analytics and data modeling for instant insights on real-time, streaming, and historical data to all users across your organization:
- Cutting-edge visualizations. Expanding both the access and use of all data sources across the organization for historical and real-time data, Arcadia Enterprise provides a responsive visual designer for users to easily define workflows and customize applications. This gives you the agility to explore data quickly and directly without having to start with extracts, cubes, or data marts. You have access to a library of over 30 visual types to choose from, for pixel-perfect visualizations.
- Multi-store support. We also make it easy for you to connect directly to a wide variety of data stores, including relational, real-time, and NoSQL. Apache Hadoop (HDFS), Amazon S3, Apache Spark, Apache Kudu, Apache Solr, and MapR-XD are just some of the supported stores.
- Modern UI. We leveraged Google’s Material Design principles, which provides a seamless workflow experience. Arcadia Enterprise features a reactive and responsive interface, so you can easily navigate and edit visuals in context. It also suggests actions and next steps that you can take, so you’re not bogged down with worrying about what comes next. You can focus on the task at hand and quickly build your visuals.
- Connect/blend data. Arcadia Data Smart Acceleration™ provides ultra-fast BI and advanced analytics with agile drag-and-drop access. With Arcadia Enterprise, you can easily connect and blend data (what we call “self-service data preparation”), giving you the agility to quickly turn raw data into an asset that can be used by the real-time, native visual analytics and BI platform.
- Accelerated insight-to-action. Arcadia Enterprise provides users with proactive alerting and scheduling features, which drive next steps via dashboard alerts and email notifications that are based on conditional thresholds on real-time data. This insight-driven agility makes it possible to quickly act on data and respond to issues in the marketplace.
If your current BI platform limits the type of data, size of data, speed of analysis, richness of visualizations, or the collaborative nature of data analysis, you should consider looking for a more agile BI platform that provides a flexible design, immediate data access, and increased data visibility for all types of users. Contact us to learn how Arcadia Enterprise can provide you with an agile BI platform that supports your diverse data delivery and usage requirements. We’re here to help you solve your complex big data problems with the scale, flexibility, performance, efficiency, and security you need to glean meaningful and real-time insights into your business.
And if you want to get a sense of our visualization interface, check out the freely downloadable Arcadia Instant, a browser-based analytical tool that represents just part of the power that Arcadia Data can offer you.