Every business possesses data, from customer and transaction information to manufacturing and shipping statistics. The vital aspect is to figure out how to use it to enhance the business’s future. One compelling strategy for companies is to use predictive analytics. This includes combing through previous information to derive models and analyses that can help predict future outcomes. Predictive analytics applies to all facets of an organization. It can help determine what customers need and don’t need and help a business augment efficiency. It can help a company spot and deal with issues when they occur. What is Predictive Analytics? To be honest and straightforward, predictive analytics makes predictions about future outcomes by analyzing historical data together with data mining techniques, statistical modelling, and machine learning. As a part of advanced analytics, predictive analytics can help businesses discover patterns within data sets and identify risks, opportunities, and tendencies. It is associated with big data and data science. With huge volumes of data hovering across transactional databases, images, videos, sensors, log files, etc., we must embrace them to derive value. Here’s where data professionals employ deep learning and machine learning algorithms to analyze the data and drive predictions. These algorithms include neural networks, linear, and non-linear progression, decision trees, and support vector machines. Surprisingly, the insights acquired using predictive analytics can be further employed within prescriptive analytics to decide future action outcomes.

1. Enabling Business
Users to Interpret
Data Through
Self-Service
Analytics

2. Introduction
Business leaders require information to drive critical decisions & expect & respond to industry &
market changes. In supposition, today’s vast stores of data should make acquiring insights
easier. But very often the reality is that acquiring pertinent data needs a request to an IT staff
already dealing with different responsibilities.
Self-service analytics is a game-changer for business people by replacing the gatekeepers of IT
tickets, data extracts, as well as report requests with technology that enables non-experts to
collect & manipulate data, apply advanced techniques, like machine learning (ML) & artificial
intelligence (AI), & produce their own visualizations & reports. The ultimate result is an
organization where business users can abide by their hunches & curiosity to unfold the answers
they require, in a timely manner that makes certain findings still pertinent & actionable.

3. What is Self-Service Analytics?
Self-service analytics technology empowers individuals without IT or data science expertise to
explore operational data & find timely & relevant insights. This proficiency enables business users,
including sales professionals, marketers, & manufacturing teams, to leverage analytics platforms
independently, eliminating the need for assistance from data scientists or IT professionals.
To allow self-service analytics, a firm implements an analytics tool, often thriving on the cloud, &
then connects it to a repository of data. Concerning traditional analytics, IT teams often had to
manage requests from business users to develop & download data extracts. Likewise, at times
sales & marketing would approach business intelligence or data science teams to generate
summaries, reports, or analysis. The “self-service” facet of self-service analytics implies that
business users can independently manage tasks without external help. The analytics software is
directly linked to the data, allowing users to autonomously choose relevant data & visualize the
platform’s tools for conducting their own analyses & creating visualizations.

4. What is Self-Service Analytics?
Leveraging self-service analytics can help business users perform multiple tasks that
previously required particular expertise, encompassing processing data sets, producing
insights, designing dashboards, & creating visualizations. A few self-service analytics
tools possess in-built AI & ML capabilities that swiftly sift through large data sets to
discover insights & unfold hidden patterns. In general, the latest integration of AI & ML
has led to a transformative impact on the proficiencies of analytics.

5. Why Is Self-Service Analytics
Important?
In multiple domains like finance, HR, operations, or sales & marketing, attaining success frequently
hinges on acquiring transparent insights into ongoing development & changes, the obstacle to
prompt action often lies in the fact that line-of-business teams are dependent on other
organizational units to conduct analytics, impeding their ability to acquire a clear understanding of
the situation.
Self-service analytics transforms this situation. Instead of submitting a ticket or sending an email,
users turn to the self-service analytics platform to directly access datasets, choose parameters, &
utilize provided tools to generate data-driven insights while creating visualizations & reports. The
resulting analysis occurs within the tool itself, eliminating the need for applications like
spreadsheets to aggregate data. This not only reduces the potential for manual errors or
inadvertent data deletions but also streamlines the iteration process. With self-service analytics,
users can easily explore data, pursue various paths of analysis, & uncover insights without waiting
for IT teams to respond.

7. Quick Decision-Making
This analytics empowers business users to bypass the waiting time for generated reports.
Instead, they can independently run queries and access the necessary data swiftly, allowing
timely decision-making based on the speed of the self-service analytics software.
Empowerment of Business Users Coupled With Increased
Efficiency for Data Analysts
Customers often praise it for its ability to drive ad-hoc reporting and analytics accessible for
employees with no technical background.
Besides, since more employees acquire freedom in running queries and performing data
analysis, data scientists and skilled analysts can shift the emphasis on simple analytics tasks
onto their core and more intricate ones.

8. Data Democratization
Self-service analytics enables data literacy and the spread of a data-driven culture by
facilitating access to data to a huge number of employees. Certainly, it doesn’t imply that every
employee has unrestricted access to vital business data, as access must be governed by data
governance policies. While one should bear in mind that the chosen security procedures might
impact the performance of the analytics solution. To overlook such a pessimistic outcome, it’s
advisable to pay special attention to tuning user access control.
Self-Service Analytics Tool Minimize The Burden on IT
Resources
Legacy tools often require a huge defence force of specially skilled developers to create reports
and dashboards. Modern self-service analytics platforms need very little progressive
maintenance infrastructure. Companies adopting such platforms need not maintain an army of
special-skill developers.

9. Acquire Immediate Answers for Any Queries
The self-service analytics platform delivers an intelligent search interface as the primary
interface for data conversation. The search interface conveys English language questions and
transforms them into SQL in real-time- this modified the paradigm as users can now acquire
immediate answers to their English questions in real-time.

10. While self-service analytics enables a broader range of business users to make informed
decisions in line with the pace of business, attaining this level of data maturity and
expanding your corporate analytical culture can be challenging. It needs to provide
business users with appropriately selected self-service tools, granting them access to
data commensurate with their business roles, and offering the required guidance.
Frequently, accomplishing this is not feasible without professional help. If you’re uncertain
about initiating the transformation to a genuinely data-driven company or encountering
challenges with an existing self-service analytic solution, Smartinfologiks is available to
deliver support and guidance.
How Can You Empower Your Business
Users to Take Ownership of the Data?

11. www.smartinfologiks.com
sales01@smartinfologiks.com
+91 9867948621