What Is A Data App?
A new way to make data more accessible.
The way we process data has changed. We moved far from manually coded data pipelines to instantly updated reports and interactive data apps. Most organizations struggle with being data-driven and almost half of businesses (46%) have struggled to recruit for roles that require data skills. But there are new ways to make data more accessible for any skill level and alleviate the data burden on BI teams. Learn what data apps look like, and why your team will love using them.
So What Are Data Apps?
Data Apps are a category of applications specifically geared towards helping teams easily manage data-intensive operations. These apps are how data science gets operationalized or set up in the format to be measured or articulated and used.
Data Apps simplify operations by allowing end-users of any skill level to interact with data effectively and in their specific context. Apps are used to access information quickly. The purpose of these data apps is to make it easy to interact with data that can impact tactical day-to-day decisions and long-term strategy without deep involvement by over-burdened analysts or business intelligence teams.
Toric’s Data Apps
In Toric, Data Apps are the end result of your data exploration - they are the reports and dashboards you create as you navigate your data. In fact, the main benefit of no-code is that you can build a working solution very rapidly, while you are still learning and exploring your data. Once you have finished creating a data app, you can turn it into a reusable template enabling your team to quickly leverage new analysis and insights fed by new data input. Subject matter experts, decision-makers, data citizens, consumers can all find data apps useful.
Unlike widgets with visualizations and limited functionality, data apps on Toric are completely customizable – from the data connectors, clean up, transformation and visualization steps all the way to the presentation layer and controls offered to your data-consumers.
3 Reasons Your Team Will Love Toric's Data Apps
Data apps are the easiest way to keep your team engaged with synchronized data that can serve as the single source of truth. Data apps are like super powerful spreadsheets that can be used to interact with views of data - either to capture new data, retrieve a result, or to analyze a dataset that continuously changes.
1. Data Apps make data interactive.
Connect and combine diverse data sources to create unique and specific views, inspect your data at the level of detail required. Include interactive elements to enable users to explore data as necessary.
In this example, there is only one data source, an excel file containing historical data from past projects to be used to determine and estimate costs for current projects. This data app brought the excel file data into an interactive view. While there may be more pages in a Historical Cost Analysis, this data app page is focused on one page - average cost per sqft.
2. Data apps are easy to update and control
A micro & macro look at the data.
To trust your data, you must trust the source and compatibility for analysis. In Toric's workspace, you can inspect and transform data as you that populate a data app. Alternatively, you can also inspect the data from a data app when necessary.
Direct data access = synchronized updates & version control.
To make your data useful, the first step is to extract it reliably. In Toric, it's easy to pull the data from its original source for further processing or storage. It’s important to note that some data changes continuously, especially when extracted from live sources (integrations.) So the way that you ingest or extract the data must contain critical information for historical value and comparison. Such as when the data was last updated and who updated it. This process is simple to do in Toric, with integrations, you can view previous revs of data used in analysis. With local files, you can swap for the latest version in the data source nodes.
All in one workspace means you all data transformation is done in one place.
Data transformation includes processes such as data type conversion, filtering, cleaning, and even data classification so you can prune and digest your data.
After all, it's not enough to have data, the data must also be clean and compatible during analysis. Poorly formatted data will cause delays in analysis which can be costly and resource-intensive. Inaccurate data is costly as well, especially when critical decisions are made using that data.
Thus the data has to be processed or transformed to ensure its accuracy. To make this easy and fast you can do it directly in the same workspace you create reports.
Enriched reports with connections that are easy to understand.
Just as the data blending example in the embodied carbon report above, any data blending or enrichment makes the data more meaningful and substantial for decision making.
This process is easy to understand and oversee, in this interactive data flow, you can directly connect different data for a deeper view instantly, giving non-technical users easier access and understanding between different data sources and how they connect.
In the dataflow view of the Embodied Carbon Data App, you can easily see an Autodesk File and EPiC energy data from an excel file were joined. When you click into the file, you can also inspect the data to ensure the data apps accuracy when necessary, bypassing manual rev control and work. If the data is not accurate, you can swap out the file for the most up to date version and keep all of the other transformations to avoid re-work.
Deeper visualizations, instantly.
Visualized data makes data easier to understand and detect patterns. They help you make the message more clear by attributing visual elements to complicated data sets.
Visual elements include charts, graphs, tables, and more. To effectively present data analysis, visualizations are essential to a business or project's success. Visual data analysis makes an impact and aids decision analysis.
The dataflow interface was built to provide a straightforward way to connect and process different data sets.
3. Data apps make your data self-serve.
With data apps people can find the answer they are looking for by themselves, in the specific context they require data. View the data in the data app view or jump into the dataflow to get additional details in analysis.
Library of reusable data apps.
Dataflows is that they live and 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.
Make better use of your data analysis team, instead of creating dataflows and data pipelines for each instant someone is looking for insights you can replicate and automate the work. Your time is spent on valuable tasks like data exploration instead of replicating and maintaining projects.
Your team will love data apps because they can engage with and get value out of their data rather than spending time and valuable resources building pipelines. Everyone is free to explore their data ask the right questions that will impact their daily decisions.
Data apps make your data interactive and foster trust that your data is accurate and synchronized across all apps’ views without overburdening data professionals. Explore our library of pre-built Data Apps to see the options available to your team. And if you see one you like, start using it!