How utilizing cloud technologies can lead to better, data-driven decisions

Terazo Team

Picture a healthcare firm responsible for safeguarding COVID-19 vaccines at the height of the pandemic. These vaccines had to be stored within a strict temperature range. Too high or too low, and they became unusable.

To protect them, the firm deployed a system to monitor metrics like temperature and humidity in real time. Alerts were sent instantly when readings fell outside the safe range, allowing experts to act immediately.

This is a prime example of how cloud technology can enable better, faster, and more impactful data-driven decisions—an approach that is becoming critical for businesses in every industry.

What is Data-Driven Decision-Making?

Data-driven decision-making means making business choices based on real-time data rather than intuition, tradition, or guesswork.

The vaccine storage example is just one way we’ve helped clients leverage data for meaningful results.

Data is everywhere. When someone visits a website, their activity is tracked. Once collected, big data can be cleaned, managed, and analyzed through cloud technologies to drive business growth.

Benefits of Data-Driven Decision-Making

Eliminates guesswork
- Decisions are based on actual behavior, not hunches.
Identifies what works—and what doesn’t
- Analyze performance and pinpoint where changes will make an impact.
Improves products, services, and customer experiences
- For example, by tracking temperature changes for our healthcare client, we saved them thousands of dollars.
- Another example: using natural language processing in a chatbot to create a human-like interaction and improve user experience.
Optimizes the sales funnel
- Track metrics like frequent visits, cart abandonment, and purchasing behavior to reduce lost opportunities.
Finds operational efficiencies
- Identify patterns that save time, energy, and money.

Examples Across Industries

E-commerce:
Measure time on site, clicks, cart adds, and purchases. Make adjustments to increase conversions.
Example: We tracked customer behavior, analyzed why they weren’t buying, and made changes that increased sales.
Nonprofits:
We built a chatbot that collects visitor information while offering assistance, then connects users to a live person. Data collected helps the nonprofit expand outreach.
Healthcare:
For the vaccine project, we captured data via storage unit sensors, moved it through a data pipeline, and performed analysis to help the client act quickly and reduce losses.

Zennify’s Approach to Data Strategy

For many businesses, getting started is the hardest part. That’s where we come in:

Discovery and Planning
- Understand client needs and goals
- Review cloud platforms and frameworks
- Build a custom integration plan
Data Wrangling and Cleaning
- Acquire raw data
- Clean it through multiple stages
- Model and document it for maximum usability
Prototyping and Iteration
- Start with a simple prototype focused on specific datasets
- Avoid centralizing all data too early to keep the process efficient
- Use iterations to solve problems in real time
Staying Current
- Follow best practices
- Stay on top of the latest cloud tools and technologies

The Outcome

Our goal is to help clients get the most value from their SaaS and PaaS investments in less time—improving decision-making, increasing agility, and boosting ROI.

Let’s Talk

If your business is struggling to make sense of its data, we’d welcome the opportunity to show you how cloud technologies can help you grow.

Schedule a complimentary consultation today.