What is a data analytics software?

Looking to learn what a data analytics software is, and how it can be useful to you? Keep scrolling to get a complete briefing on it—and how you can get started with it.

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Definition of data analytics

The volume, velocity, and veracity of data generated today is incomparable—and extracting the maximum value out of it is paramount. The significance of analytics is higher now than ever.

Data analytics is the business of deriving meaningful insights in the form of patterns, relationships, and trends, from diverse data sets. It involves the application of both quantitative and qualitative methodologies.

Data analytics software enables collecting, cleansing, storing, analyzing, and reporting of data on any given scale.

The business case for data analytics

The key business objectives of any organization are to reduce costs, increase profitability, and improve risk management.

A successful business can achieve all three with timely insights on identifying new growth opportunities, business process improvement, segmenting target markets, and planning future roadmaps.

Robust data analytics software that serves these insights quickly and accurately is a major enabler of high business performance and growth.

What can you do with Data Analytics?


Strategize in real time

Actively plan your campaigns, operations, and budgeting with up-to-date data. Easily collaborate across all levels for continuous data collection, preparation, analysis, and reporting. Understand your actual performance, course correct deviations, and predict scenarios for more effective business continuity.


Understand the actual results

What were your sales last quarter? Who utilized customer service the most? Data analytics allows you to constantly reflect on "what's happened" and "what's happening" by measuring and monitoring KPIs using a variety of self-service BI visualizations.


Plan your future roadmap

Identify trends and anomalies from past performance. Gather context by analyzing data collected from disparate sources. Drill down even further to identify drivers that impact business outcomes. Use them to predict future events via smart forecasting.

Who uses data analytics?



The shift to data-native culture is pushing C-level executives to reinvent their strategic and business outlooks. Integrating data analytics across enterprise functions can give them unprecedented visibility into enhancing operational efficiency. These analytic insights also drive the proactiveness needed to address gaps effectively and subsequently future-proof the company.


Marketing & sales

Analytics provides a complete view of prospects' journeys—transcending the old linear concept. Marketers can track customers all the way from initial interest to final purchase. The detailed insights available on consumer behavior and preferences help in creating personalized interactions with them.


Human resources

Analytics-driven organizations can be predictive, rather than reactionary, in understanding their employees. Data insights empower them to hire the right talent, optimize benefits for employee retention, and identify areas for skill development. It also helps HR to seamlessly collaborate with other departments for workforce planning and monitoring.



Finance teams understand client payment behavior, track cash flow, handle profitability and margin analysis, and run revenue forecasting. In a regulatory and economic environment that's more challenging than ever, analytics empowers organizations to perform highly accurate risk assessment and management.


Customer service

To achieve higher customer satisfaction and loyalty, analytics can assist in tailoring customer experiences by predicting their needs, picking up on friction at customer touchpoints, and personalize incentives for retention. Insights on support agent performance can be useful in reducing latency and bridging skill gaps.

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Capabilities of a data analytics software

data analytics

Data collection and management

Data which is available in any form (structured, unstructured, semi-structured) and from anywhere (files, feeds, local and cloud storage) can be blended and merged, at any scale and complexity. The collected data is further organized in a standard format, to make sense out of it easily. It's also imperative to exercise fine-grained access control, to ensure data privacy and security.


Data analysis and reporting

Useful insights can be discovered through in-depth data exploration. They can then be meaningfully presented for consumption in the form of visually rich reports and dashboards.


Data sharing and collaboration

The value of insights gained is only realised by sharing them with appropriate business stakeholders in multiple ways—like email alerts or embedded dashboards. Facilitating real-time collaboration between them drives quick and informed decision-making.

Kinds of data analytics


Self-service analytics

This empowers business users to analyze data and generate reports on their own, with minimal training and IT support. Here the data access is more straightforward and analytics is facilitated through easy-to-use interfaces.


Augmented analytics

The large-scale automation of data preparation, analysis, and reporting facilitated by AI-driven technologies—such as machine learning (ML) and natural language processing (NLP)—has enabled the mining of insights out of huge datasets that was never possible before.


Embedded analytics

Integrating analytics natively, within the business workflow, into points of data consumption—applications, portals, products, etc—offers seamless insights for making swift decisions in real time.

Benefits of data analytics software

  • Creating fail-proof business strategies based on detailed insights and highly accurate predictions
  • Identifying growth opportunities that would be almost impossible through legacy methods
  • Holding on to competitive advantages through constant market awareness
  • Proactively spotting and fixing gaps for seamless business continuity
  • Widening the scope for innovation by integrating with emerging technologies

Best practices to remember

  • Embrace analytics throughout your organization's culture
  • Re-engineer legacy methods and systems within the latest frameworks
  • Stay in tune with advanced analytics features and capabilities
  • Work with suitable vendors and focus more on your core business
  • Thoroughly evaluate the expertise of potential partners
  • Continuously refine and redefine your business' approach to analytics

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A cloud BI pioneer for over a decade, Zoho Analytics is now used by more than 10 million business users, and 100,000 businesses in 120+ countries around the world.

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