While making a paradigm shift, businesses usually look for solutions that best suit their business model in the long run. And when it comes to identifying and bringing in innovations, Business Intelligence has gained momentum in the global market. It’s solely based on how enterprises analyze the data, utilize modern technologies and strategies which decide what the actual limit of an organization is.
At this point, Business Intelligence makes a smart entry as an ideal way out for CIOs to seamlessly revolutionize silos of business data. Business intelligence is here to stay for tackling the growing data complexity concerns throughout global businesses and wide industry verticals. But before we dive deeper, let’s get a clear idea of the impact of business intelligence in today’s tech-driven landscape. So, without any further ado, let’s get started!
Understanding business intelligence and why it matters
Business intelligence helps to transform data into valuable and actionable insights that keep enterprises informed about business decisions. Business intelligence assists people in organizing the data so it can be accessed and analyzed in a hassle-free manner. This enables the decision-makers to quickly get the information they are looking for, empowering them to make informed and smart decisions.
Apart from this, there are a lot of other things that business intelligence is helping the business owners with- maximized organizational efficiency, faster data analysis, data-driven business decisions, better employee satisfaction, and get trusted yet governed data.
How business intelligence tackles data complexity issues?
Data verticals are expanding exponentially and in today’s time, Not only there is data, but there are more and more data sources than ever before. Besides this, the value to unlock that data and utilize it for making accurate and efficient business decisions is also on the rise.
When it comes to business users, understanding the complex data and unraveling its true potential is the only way to gain a competitive edge in the market. Similarly, for IT firms, complex data can be bothersome for many programs, resulting in multiple types of challenges in data management while hindering the overall system performance. At this point, investing in BI tools is a worthy decision that helps you smartly simplify the data and gain insights from data.
Business intelligence is equipped with automation which minimizes the workload as it puts particular tasks in auto-set mode and it further makes the wide range of data available at your fingertips and makes your job easy. Additionally, backed by self-service tools, business intelligence is playing a vital role in tackling data complexity issues. The self-service tools usually allow only necessary queries to be answered and minimizes the unnecessary gathering of data reports. BI even makes the job of developers easy and they need to only set up the platform for self-service and even non-technical people can access and manage the data. These tools even help in minimizing the time elapsed while making reports or generating insights from the report. The tools are backed by decentralization which has established the way to less laborious approaches for report generation. It even minimizes the rounds of editions that were otherwise controlled by IT and will presently be self-handled with the varying and accommodative tools.
All these advancements have led to overrule the traditional methods of analytics that involved a business user whenever a report was to be prepared or analysis was carried out which eventually hampered the efficiency.
How Seasia leverages BI to address data complexity in real-life
Whether it is the business data or the customer's data on a global level, Seasia manages data silos on a daily basis. Realizing the true potential of business intelligence, we simplify Business Analytics for Complex business data, which helps us optimize speed for handling larger data sets and merging the Business Analytics process. As a result, it assists our teams to reduce the multiple steps in data preparation and reducing the burden of Business Analytics throughout the workforce.
Emphasizing more on our business analytics process and backed by the latest technology innovation into our business model, we have succeeded to a great extend in eliminating multiple steps throughout our business analytics lifecycle while streamlining the overall data management within and beyond our organization. In the long run, it is helping us to reduce the requirement for compacting, aggregating, and indexing data and minimize the patchwork of numerous tools that are usually required for analyzing complex data.
A long way to go!
In the years to come, we can expect a lot of advancements in the BI landscape- we’ll be experiencing augmented analytics backed by Machine Learning which will be guiding users on their queries into the data. This is going to be an ideal blend of business intelligence and analytics which will welcome more smart and surprising outcomes for global businesses and the entire digital space. Counting on BI tools and services holds the potential of catering to the requirements of all sorts of businesses and industry verticals in the world.
For successfully implementing and scaling business intelligence throughout an enterprise, you’ll have to articulate a strategy, a roadmap, and allocate resources. For businesses who don't have in-house talent for working on business intelligence, outsourcing will ensure reliable and professional development. You can also connect with Seasia experts who can guide you with how BI can be implemented into your business model and manage the data in a simple and streamlined way.
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Yashu Kapila is working as Vice President at BugRaptors. The best part of her role is managing key client relationships, setting up and building large testing services and release for projects spread across the globe. She has diverse experience in release management, consulting, operations and presales. She holds the expertise in SDLC, Project management, Process Definition, and CMMi. She is also involved in creation of WBS, test plans, user requirements study, part of wireframes, resource allocation, daily scrums, monitoring and control. She drove CMMi L5 v1.3 initiative with successful implementation of the model.