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Corporate Self Service Analytics: 4 Questions You Should Ask Yourself Before You Start

Corporate Self Service Analytics: 4 Questions You Should Ask Yourself Before You Start

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:

1. How do I Select the Right BI&A Architecture for My Business?

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:

  • Insight: Advanced, agile BI&A platforms offer quick insights and analytics in different areas of your organisation. They allow you to improve your performance by offering innovative solutions. In addition, they accurately identify data patterns and present them in an easy-to-understand way, enabling businesses to make decisions based on solid facts and with more confidence. These insights enable businesses to predict and test potential outcomes, greatly reducing the risk of failure and loss. 
  • Autonomy: Analytics should be more widespread and easily accessible at different levels of your organisation. This will allow you to explore critical information and devise insights with the help of self-service data discovery and data prep tools. Doing so will allow you to promote an internal, information-driven culture, making your business more responsive, assertive, and nimble, while the decisions will be more fact-based. 
  • Analytics Trust: The analytics platform should be capable of providing trustworthy, reliable, consistent insights. However, businesses need to keep in mind that transitioning to an advanced BI&A platform shouldn’t be done on the expense of inaccurate, untrustworthy insights and information. In any case, ensuring the credibility of analytics platform’s outputs is of essence before you can go for an organisation-wide implementation. 

2. How Do I Choose the Right Analytics Platform? 

There are a few things you need to keep in mind for choosing the right analytics platform:

  • Approach: Based on the type and magnitude of your business operations, you must decide whether you should keep your data on premise, host services in the public cloud, or opt for a hybrid approach. 
  • Cost: Another important aspect to consider is that your BI&A platform must be capable of catering to the needs of multiple users without incurring additional costs related to customization. The platform should natively support data prep and migration. Moreover, the expenses should only cover the costs of what you use.
  • Scalability: Make sure you evaluate the capability of the analytics platform to support any number of users, ranging from a few hundreds to thousands. Enterprise-level businesses require a complete set of features to fulfil their different business intelligence needs. 

3. How Can I be Sure that My Data is Secure?

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. 

 4. What Operations Capabilities Are Recommended? 

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.