Businesses driven by data

Why decisions in businesses fail when not driven by data

10 powerful OQLIS modules explained.

Part of the OQLIS 10-series blogs in celebration of a decade in business.

Throughout the last decade of its customer-centric existence, OQLIS. The Data Insights People have discovered exactly what their customers need and what they are trying to achieve when it comes to business data analytics. And they are now sharing their secret sauce. Businesses make better decisions through data analytics and visualization. But how can data analytics help businesses make better decisions?

Before we get more technical and practical, it is crucial to understand what organisations want when it comes to Business Intelligence Solutions. These are some of the fixes businesses desire:

  • A unified version of the truth. A central data source that allows them to make the right decisions
  • They come to us to create an integrated single portal that their customers or their ecosystem to log into to see that unified version of the truth.
  • They want to generate automatic reports and,
  • They want their data insights accessible anywhere. On the phone, the web, and all the time.
  • Lastly, they want a solution that is scalable and distributable.

But how can data analytics software provide solutions to all of these needs? For the last 10 years, OQLIS has built a complementary suite of 10 modules that allow customers to solve their enterprise’s business problems, no matter what they are.

OQLIS data connection software integration

1. Connection

Connect OQLIS data intelligence software securely to all the databases you want to monitor and derive insights from. Supported database connections include (but are not limited to): Microsoft SQL/Azure, MySQL, PostgreSQL, Amazon Red Shift, Oracle, CSV, and Microsoft Excel.

2. Data Model

Once the connection is secured, we can now model the data. OQLIS has opted for pure SQL, which allows anybody of any skill level to start working with their data.
The software provides the ability to select different Tables from your previously created Database Connection. The data model tab provides the functionality to use basic SQL syntax to extract only the data you need for advanced analytics and business intelligence.


3. Explore

Now businesses can explore their data on the system and start building those insights. An OQLIS Explore is essentially a data visualisation, this could be a bar chart, a pie chart, a Google map, and many more! Raw data shows you NO true value, so to drive valuable insights you need a data visualisation solution that seamlessly interrogates data, and builds reports and dashboards that show you business insights at a glance.


4. Dashboard

Fourthly they start building those beautiful dashboards. This is usually where traditional reporting systems end. The user has connected the data source and built a dashboard and now they are done, but this is seldom sufficient. If you think about it, dashboards are the tip of the iceberg, but people don’t know what is underneath. There is however data engineering, and data storage underneath, and there are all the business logic and business rules that sit inside of that data model.

5. Component

There are various modules that OQLIS has built over time, making it’s offering much more than mere data analytics software. One of the components that was built recently is a component that allows users to enter values in a data grid on the dashboard, and have that write back to the source system. With this component, users can update data directly from a dashboard view. Add, edit, or delete records from your database, on your dashboard. An absolute game-changer! The dashboard becomes dynamic and interactive while writing back into the core systems.

OQLIS Dashboard Reporting

6. Schedule

Users can automatically schedule reports and distribute them across their co-workers or customer base. OQLIS has improved scheduling to include exporting to Excel, PowerPoint, CSV, and PDFs. It allows users to have a specific dashboard scheduled for them regularly. Users prefer schedules to be sent to them on a specific day or time where they can analyse the data from the convenience of their email inbox.

7. Automation

As they were already doing all this calculation on data, OQLIS made it possible to build in the business rule to alert when needed. They did it through the automation module, with scheduling capabilities. It calculates a value at a given schedule and tests the criteria defined by the user. For instance, if the sales target reaches a certain threshold, you can trigger an alert that the system then sends messages via phone, WhatsApps, email, and more.

8. IoT

When you think about the world of the Internet of Things (IoT), you would surmise that an IoT platform is needed to collect data. But the reality is that all you need to do is provide an endpoint for sensors to send their data to, and then you need a platform like OQLIS, to build the dashboards on top. OQLIS saw that opportunity where their customers wanted to augment their business data with sensor data. They wanted their sensor data platforms to directly plug into OQLIS (in real-time), and then build their dashboards on top of that. It provides an IoT module that allows users to ingest data from external sources like sensors, webhooks, and more.

9. ML & AI

Machine Learning and Artificial Intelligence are very hot topics in this day and age because of their powerful impact on digital transformation. Three years ago OQLIS came to the realisation that in order to solve a bigger slice of the data pie, they had to build ML and AI into OQLIS. This module helps businesses to build machine learning models, train the models, use and trigger those models, to run and predict values as they come in, in real-time.

OQLIS Unify - custom code integrations in Python

10. Unify

OQLIS offers a complementary suite of modules that allow users to solve an enterprise’s business problems, no matter the challenge. The addition of the Unify module is revolutionary in terms of problem-solving for its users. Business data lives in various locations such as databases, APIs, or various other systems. Before Unify, custom code integrations in Python had to run on a server somewhere, without a way to monitor its status or look back at activity.

 

The OQLIS team started building the Unify module to run these integrations inside the platform, basically leveraging Docker and running an isolated Docker environment with custom code that users can input into OQLIS. This has solved a lot of customers’ problems.
They can build custom integrations into different APIs across business systems and consume the CloudFlare logs through this module.

 

In the wise words of the late basketball coach John Wooden, “It takes time to create excellence. If it can be done quickly, more people would do it!”. Leverage a decade of data intelligence excellence, making a difference in thousands of users and businesses in their day-to-day operations.

For tenfold returns, reach out to the Data Insights People today.

Contact us on [email protected]