Solutions Engineer
Tanay Shah

Accessible Data Analytics - Bypassing The Technical Barrier

It’s not easy to become data-driven; there are significant barriers to overcome. According to an executive survey of fortune 1000 companies by New Vantage Partners only 24% of executives thought their organization was data-driven in 2020. But this does not need to be the case. Learn how no-code data analysis tools break down the technical barrier to enable organizations to make data analysis more accessible to non-technical individuals. 

What Is The Technical Barrier? 

A large part of the skills required for data analysis includes specialized skills such as programming in the setup, exploration, and maintenance of data stacks. Data analysts and data scientists spend a large portion of their time problem-solving to distill the information and make it accessible for analysis. Sometimes entire teams are dedicated to building solutions to extract and convert data for analysis and problem-solve for data pipelines and problematic cases for data extraction and transformation. 

We started to collect more data than we know what to do with, and it is not scalable to use specialized talent for all data analysis. Thankfully new innovations and improvements in handling data started to emerge in tech, enabling access to data exploration to a more significant number of individuals. 

3 Ways Toric Makes Data Analysis Accessible.

With no code tools and single data pipelines, data analysis is more accessible and easier than ever.  Toric uses an interactive dataflow chart interface, making the process for building and maintaining data pipelines much more simple than building custom code or connecting and maintaining several programs.

With a visual representation of a data flow anyone can jump in, connect different data sources, transform their data, build smart data app reports, and make the process reusable. In other words, anyone can focus on analytics rather than be bogged down by technical efforts. Here's how no-code takes the complex technical skills required to build data pipelines and simplifies the process:

1. Direct Data Connection & Transformation.

Get connected directly to your tools.

The interactive dataflow offers several ways to connect with data. You can drag and drop data from your computer within the dataflow, or connect to your data using an integration. Toric can process and transform millions of records interactively within the dataflow interface. This interface is flexible enough to pull complex data in ways spreadsheets can’t. One example is the Toric Revit integration, which allows users to interact with 3D views from CAD files to pull data on specific components for analysis.

View all available integrations.

Example of a Toric Integration - Connect directly to Revit to pull data from models to use in analysis.

No need for an additional warehouse. 

Your data is hosted in the cloud. There is no need for an additional data warehouse when all your data can be stored and within the platform. Due to the nature of the interface, you do not need to clean or process your data before uploading it to Toric. Toric is flexible to act as your data lake even if you chose to use a different program for other essential data pipeline functions.

Clean, transformation, and blending data in one place.

The dataflow interface was built to provide a straightforward way to connect and process different data sets.

A dataflow diagram is traditionally a representation of how your data connects, but you can instantly connect different data for a deeper view in this interface. An added benefit is that this tool can give non-technical users easier access and understanding between different data sources and how they connect.

example of toric dataflow
Example of a Toric dataflow - data is connecting using interactive nodes

In this workspace, you interact with your data more flexibly through nodes. These nodes enable you to perform individual functions, including data cleanup and transformation. Within this interface, you can inspect the data in each individual node using the node-inspector panel. 

You do not have to think about the order in which you clean and transform your data.  In fact, you can clean up your data while you build your dataflow. An added benefit of utilizing nodes is the option of classifying data types so you can prune and digest your data in new ways. 

2. Intuitive Data Analysis & Smart Reports.

Analyze data and build reports at the same time.

As you explore your data using the nodes in the dataflow interface, you can take advantage of the data app panel to build elements of your report in the same view you are using to explore your data. Instead of switching between applications, you can provide context to your data exploration as you build your dataflow. 

Create visualizations and interactive data app elements directly in your dataflow.

Taking your data analysis further, the data app panel enables you to create interactive data visualizations.

Not only can you create graphs, bars, charts, and more, but you can also do it while you explore your data and make it available for reports as you explore your data.  See the example below of a rough order of magnitude report as an example of an interactive data app. The data used is pulled from two sources, an Excel Spreadsheet and a 3D model from Revit. Within the data app you can explore different scenarios using the interactive elements. 

3. Re-usable Data Apps.

Take advantage to a unique feature of no-code dataflows. Dataflows sit on top of your data. It’s easy to create a dataflow template and replace data for consistent data flows and reports with just a few clicks. Try it for yourself using our pre-build data apps.

Key Takeway

Data analysis is performed to distill valuable data insights and inform decisions. It requires a highly specialized skillset to distill data in conventional data pipelines, but with no-code dataflows and single data pipelines it's possible to bypass the technical barrier and dive in to explore the data for insights. 

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