5 growth drivers a Modern Analytics Platform delivers

With a massive explosion of data across sources, organizations have embraced analytics to extract meaningful insights for better business decisions.

BI and analytics vendors are constantly propelled to innovate due to the variety of needs an enterprise has, when it come to crunching and analyzing high volumes of data from multiple sources.

Wherever your organization is on its BI and analytics journey, it’s important to take stock of your existing analytical systems to stay current. The following framework can be used for this assessment.

The “ingestion-to-action” framework is designed in line with an enterprise-BI workflow. In this blog, we’ll learn how a modern BI and analytics platform drives growth across these five stages, and detail the innovations happening in these domains.

Break data silos

Enterprise businesses are faced with two major challenges when it comes to data silos: 

  • The diversity in data and data sources
    Apart from in-house data, vendors, customers, distributors, etc. are becoming major data generation hubs for modern enterprises that’ve deployed their systems at these locations across geographies. The data they produce gets locked up inside data warehouses, databases, business apps, cloud storages, and more.

  • Data pipelines
    Building and maintaining a data pipeline is usually not an enjoyable experience, and handling modifications is becoming a cause of concern for many enterprises. The ballooning data needs call for simple yet powerful data pipelines.

ETL tools were built to address these challenges. However, with more data to process and with NoSQL databases gaining popularity, the in-memory and monolithic architectures couldn’t handle these heavy transformations. This has opened up opportunities for ELT.

Interestingly, modern BI and analytics platforms have consumed ETL and ELT layers into their tech stacks. Native connectors can ingest data in a few clicks. Platforms are also engineered to work seamlessly with 3rd-party data pipeline service providers. The built-in API stacks also enable enterprises to get data from any source.   

Data preparation and management

Nearly 80% of analysis time is spent on data preparation. This has become a worrying trend for enterprises, and they are on the lookout for solutions that simplify the data preparation process.

Some modern BI and analytics platforms are weaving AI and ML-powered data preparation capabilities into their stacks, empowering users to integrate, model, clean, transform, enrich, and catalog data. The augmentation of automation is also creating a more business-friendly data preparation and management layer. 

Here’s an example from Zoho DataPrep, our AI-powered, self-service data preparation software solution.

Unified business analytics

With more citizen data scientists embracing analytics, it’s important to shorten the time to insights for quicker and better decisions. Since the complex interdependencies within enterprises calls for end-to-end business insights, unified business analytics is a game changer!

It serves users with prebuilt analytics that covers data models, KPI metrics, reports, dashboards, and domain-trained NLQ that enables them to jump-start their analytics instantly, cutting down their time to insights.

Here’s one of the many prebuilt dashboards users get by integrating Salesforce with Zoho Analytics.

 

The below dashboard smartly blends and analyzes data from Salesforce, Zendesk, Sales IQ, and from ERP software hosted on AWS. This enables enterprises to understand the cross-functional impact of variables influencing their business.

Data democratization

When data analytics was in its embryonic stage, IT teams had to glean data, analyze it, and distribute insights. To ease the load on IT teams and to drive adoption, self-service features such as drag and drop were introduced. This rapidly transformed into an era of augmented analytics.

Select BI vendors have successfully leveraged AI and ML to build amazing capabilities into their platforms—for instance, conversational analytics, built on a NLP framework. Users with no technical know-how can get into immersive conversations through a chat-like interface and instantly get contextual insights.

The built-in NLG capabilities give users more firepower by serving auto insights in the form of narratives.

Fostering collaboration

Collaboration is the key to accelerating BI adoption. To facilitate this, BI vendors started supporting users to embed reports and dashboards across points of consumption. Some vendors took this further by delivering NLP and NLG capabilities at these points, thereby speeding up analysis and decision-making.

With data storytelling gaining steam, collaborative analytics is on the rise. The built-in LCNC capabilities are enabling enterprises to humanize data interactions by customizing and presenting insights in compelling ways.

Here’s an example of a purpose-built analytics portal crafted by simply dragging and dropping elements into the built-in editor.

Summary

Modern BI and analytics platforms are revolutionizing the BI workflow with a stream of advanced analytical capabilities. Some enterprises are taking full advantage of this and are transforming the way decisions are being made.

As one of the frontrunners in this industry, Zoho Analytics has been consciously investing in people and technology to engineer enterprise-grade analytics for corporations worldwide.

Check out how Zoho Analytics can be the best fit for your enterprise analytics needs. Sign up now!

Also, check out our webinar on 5 growth drivers a Modern Analytics Platform delivers.

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