The fast-changing business models, dynamic markets, and increasing customer expectations have forced enterprises to keep pace with these changing requirements by empowering their employees with the right data at the right time. With more number of businesses competing with data, there is a greater need for employees within the enterprises to gain better insight into them and become more agile by ensuring that information is easily accessible to them.
As a result, organizations that used to rely on traditional Business Intelligence tools, which required heavy assistance from the IT teams, have shifted their focus towards self-service BI and analytics to meet the requirements of today’s agile and data-driven businesses. Self service Analytics are key for businesses that need to have data at the core of their business decision making, operations, and effort optimization.
Let’s find out more about how self service analytics is playing a significant role in changing the business landscape.
What is Self Service Analytics?
According to Gartner- “Self Service Analytics is a kind of business intelligence in which host of business professionals get the required support and motivation for performing queries and generating report with minimal IT support.”
With vast amounts of structured and unstructured data generated by enterprises, both big and small, there is a greater necessity to extract greater value from this information. Thus, self service business intelligence has evolved as the right solution to meet the growing needs by allowing everyone (including non-technical people) for accessing and analyzing the data for making the right business decisions without the involvement of their IT department. Self Service Analytics provides an intuitive user interface so that users can focus on deriving insights from data and not just worry about technology.
Top Reasons Why Businesses Need Self Service Analytics Tools
Boost the bottom line
Enterprises need to clearly define their objectives before making an analysis to get the maximum value from their data. By leveraging the right data, the team should be able to get precise answers to specific questions, which can save their valuable time and money. With the use of self service business intelligence tools, it’s possible for employees to easily have access to the data to find answers to their questions. In case the results are not relevant, they can still run the query without the assistance of the IT department. When the employees are empowered with data, the decision-making is faster, more accurate, and addresses the current business needs.
Allows for democratization of data
With self service business intelligence, members of the team can have quick and easy access to the same data, which makes the process of decision-making faster. Everyone involved in the project can get information with business intelligence turning democratic which can be beneficial for the employees. Rather than depending on data scientists and IT experts, who may be going through spreadsheets for finding vital clues about services, self service business intelligence provides equal opportunity to all the business users in the team.
Assists with on-demand reporting
Ad-hoc reporting may be used to answer specific questions and analyze only specific data which is a more popular option among enterprises. Self service analytics tools address this need by enabling users to have easy and instant access to valuable bits of information for analysis.
Growing popularity of visual analytics
With a visual based intuitive interface, users can have better options for viewing, interpreting and analyzing key information. Dashboards and reports can be created easily with the use of powerful and intuitive visualization tools through charts, widgets, pivot tables, metrics related to KPI etc. Using self service tools, it’s possible to slice and dice the data to go down to the minutest of details and even change appearances using templates and chart types.
Improved flexibility with improved IT governance
Today, both IT and business users may not be able to depend on each other to meet their different reporting requirements. Self service BI tools offer a high degree of flexibility to perform a wide range of tasks with the creation of personalized reports, real-time insights on the required data and thereby take quick actions.
Trends in Self Service Data Analytics
Increase in self service data preparation
Using self service data preparation tools, business users can combine data through different sources on their own with just a few clicks using the intuitive user interface. The ability to draw insights using data is much faster compared to traditional BI tools which may take a longer time. The technologies used for self service data preparation help in automating the processes which reduce the users’ manual work involved in data finding and cleansing, data categorization and conversion. With the increasing demand for visual analytics tools and BI, there will be greater emphasis and growth of self service data preparation tools among enterprises.
Natural language set to play a pivotal role in Analytics and BI
With more number of users demanding improved integration of data search functionality, natural language has become essential for self service tools. Users prefer to find data quickly and create natural language queries and perform operations by asking specific questions instead of writing SQL queries for making the search process more intuitive. In the coming years, search will become a key component of self service tools and users would be keen to learn different ways of using search functionality for interacting with the data.
Cloud and on-premises applications will result into data-driven leadership
In the coming years, cloud will continue be of greater significance in BI as a source of business intelligence and act as a BI platform as well. As a result, many users of business intelligence will find it convenient to connect, integrate and slice and analyze data from sources which may be external to the current data warehouse. Thus, data may be extracted not only from Excel or CSV files, but also through cloud-based applications including Google Doc, Analytics and other cloud resources to provide a more detailed view of the company’s KPI against other external factors in the environment.
Conclusion
Self Service Analytics is going to be more widely used in the coming years – simply because it offers meaningful and faster insights using data. It helps business leaders in creating and managing reporting and in embracing the best data quality practices, without dependence on the IT or technology teams.