Today’s customers are socially driven and more value conscious than they were ever before. Believe it or not, everyday customer interactions create a whopping 2.5 exabytes of data, which is equal to 1,000,000 terabytes, and this figure has been predicted to grow by 40 percent with every passing year. As organisations face the mounting challenges of coping with the surge in the amount of data and number of customer interactions, it has become extremely difficult to manage the huge quantities of information, whilst providing a satisfying customer experience. It is imperative for businesses and corporations to create a customer-centric experience by adopting a data-driven approach, based on predictive analytics.
Integrating an advanced self-service analytics (SSA) environment for strengthening your analytics and data handling strategy can prove to be beneficial for your business, regardless of the type and size of your enterprise. A corporate SSA environment can assist in dramatically improving your operations capabilities, as it provides an in-depth understanding of consumer data. This, in turn, facilitates your workforce in taking up a more responsive, nimble approach to analyzing data, and fosters fact-based decision making rather than on predictions and guesswork. Self-service analytics offers a wealth of intelligence and insights into how to make sense out of data and build more intimate relationships for better customer experience.
Why Businesses Need Self Service Analytics
With the increasing costs of effectively managing Big Data being the reason of perturbation, businesses need a platform that can aid in scaling without breaking the bank. In addition, there is a major concern for the security level of data. Most businesses lack the talent and knowledge regarding different business intelligence and analytics (BI&A), and often end up choosing the wrong model unfitting for the size and operations of their business. This results in inaccurate data insights, leading to IT bottlenecks, disconnected analytics experiences, security and governance risks, and additional expenses.
What businesses need is a comprehensive IT solution offering a broader range of data sources and self-service analytics capabilities. In addition, the analytics platform must be uncomplicated and easy-to-use, while at the same time it should be able to meticulously handle complex analytics functions.
To ensure that the self-service analytics platform you are considering choosing is the right one for your business, you need to ask yourself these four questions before you start:
You need to choose a platform that offers deeper insights, accurate analytics, and complete autonomy trust to help your workforce develop a better understanding of data and extract crucial information, whilst reducing the amount of work and costs. For selecting the right BI&A architecture for your business, you need to determine the relative importance of these three attributes:
There are a few things you need to keep in mind for choosing the right analytics platform:
Most organizations face problems in coping with two key needs: IT needs for ensuring secure operations and business user needs where they have to interact in real-time with their own data. Businesses shouldn’t let BI restrict their functionality; they need to figure out ways to bridge the gap between legacy BI systems and desktop tools. One practical way is to implement a single complete BI&A platform. This will ensure that all your business users and data are centralized in a managed and self-service secure environment.
This is probably the most important question you need to have a clear understanding about. To ensure the successful implementation your BI&A initiative it must be easy-to-use, while capable of handling complex analysis and generate accurate results in a simplified manner. It is important that your workforce, without formal knowledge or technical background, is be able to use the BI&A platform, which will save time and energy spent in regularly engaging tech support for trivial issues.
When dealing with complex combinations of data, your BI&A platform should apply a range of analytics techniques and come up with better, more impactful insights. Broader sharing of data insights and quick response to user queries for data will enable achieving business benefits relatively easy. Moreover, it should offer high product support, top-notch product quality, and ease of upgrade and migration.
The breadth of analytical computations, along with the number of data sources and volume of data, is growing at an exceptional pace. Businesses and enterprises require flexibility in order to manage the analytical life cycle, from beginning to the implementation of huge numbers of existing and new analytical models that address industry-specific and functional issues of your business in a scalable, secure manner. For this, data scientists need SSA environments instead of simple BI solutions to conduct predictive analytics in an effective manner.