Data’s impact on business is only gathering momentum. Key trends in business intelligence for this year include a focus on the Internet-of-Things (IoT), highly improved cognitive solutions and the rise of insight-driven organizations. With such growth in potential uses, sources and types of data, enterprises of all sizes are now facing increasing complexity when it comes to collection, management and analytics. Increased complexity, in turn, makes for new challenges for decision-makers and data scientists.
The rapid rise of connected devices and business ecosystems has resulted in an increasing number of disparate data sources, coupled with a growing diversity of data types, all leading to the increasing complexity of data.
The challenges of more data and source types
A recent whitepaper published by Aberdeen and Sisense on integrated single-stack business intelligence solutions points out the challenge of data complexity, citing the following trends among survey respondents:
-- 93 percent of organizations cite significant data growth over the past year.
-- Respondents use an average of 30 unique data sources on a regular basis.
-- 40 percent of respondents analyze unstructured data from both internal and external sources.
While larger data sets can provide deeper and more impactful insights, these also have major implications on the resources needed by organizations, especially when it comes to time-consuming and potentially expensive data collection, storage and analytics involved. It can be extremely heavy on resources to manipulate and visualize this data into formats that are quickly and easily understood for decision-making. As a business’s data begins to grow, the more likely it is to experience these challenges.
Implementing strategies to properly manage complex data is not an easy task, either. Enterprises often spend millions of dollars each year on dedicated infrastructure and software solutions to crunch numbers and process information. In addition, these big organizations have traditionally hired specialists and data scientists to regularly maintain their complex pipelines.
However, the current trend is moving toward self-service analytics platforms, which promise ease-of-use through visual approaches to managing data. The downside is that not all of these solutions are capable of handing complex data sets, which often require parsing vast amounts of data from multiple sources. This puts enterprises in a difficult position, forcing them to make compromises based on their priorities: is it more important to be able to generate engaging visuals using solutions with simple UX, or to be able to generate in-depth insights from more complex solutions?
Performance without the complexity
Fortunately, there are several new tools that offer tangible solutions to this issue so that organizations large and small don’t have to compromise on quality. The key here is managing complex data through simple and straightforward solutions that don’t require expensive hardware, software and analysts to run.
The single-stack BI solution empowers businesses to combine all disparate data sources in order to gain a deeper insight for just about any application – all without complex coding required. These tools support detailed insights, while also maintaining clear visualization, which makes the data easily digestible for both IT experts and non-IT professionals. Such speed and simplicity in managing data allows for businesses to make the best data-driven decisions with minimal latency, thus ensuring agility in operations.
Bime, for example, is one highly respected option for those working with large teams, since it allows each end user to blend datasets that are relevant to him or her in one single report or dashboard. This ensures that everyone can stay up-to-date with important insights, communicate easily with one another, and make fast decisions in real-time within the platform.
The aforementioned Sisense, moreover, offers a way to create and manage complex data models from simple sources, all in a drag-and-drop user interface. Even better, Sisense can run on standard office-grade desktop computers, which reduces the costs involved in setting up a BI stack. Sisense won a coveted 2016 Red Herring award for innovation earlier this month.
Another platform that can help you optimize your BI strategy and acquire in-depth insights is Adaptive Analytics, which employs a software as a service (SaaS) delivery model that has many advantages over the traditional BI options. Cloud delivery enables faster deployment, and the user-friendly interface intentionally matches that of Microsoft Excel, making it familiar and simple for non-IT experts. Just as importantly, Adaptive’s subscription-based model is highly cost-effective, since the cloud platform updates automatically, saving on deployment and maintenance costs. According to the company, it can provide up to 75 percent savings from the costs traditionally associated with BI.
Data is growing, and so should your capability to manage it
Again, managing your complex data can be a daunting task. Luckily there are new solutions that allow you thoroughly understand your data, while collecting the most detailed, real-time insight, as well. Self-service solutions now empower you with the capability to identify and analyze important trends in your data in a straightforward interface that will help you make the most well-informed business decisions.
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