Before understanding your data, I would say understand, define, and scope your problem first. Many projects fail (i.e., take longer and cost more) because teams jump into problem solving without taking the necessary time to assess the pain they are trying to solve. In some instances, this may be plainly obvious, in some other instances, perhaps not so much. Once you have a solid scope definition for your particular issue, then you can start looking at the data available within your organization that you could potentially leverage on to start framing your decision-making progress. Once you identify which data you could use, then the process of understanding your data really begins, from a data management point of view, that is.

First, I'd engage with the engineers to understand their specific challenges, goals, and the types of decisions they need to make. Next, I'd work with them to identify the relevant data sources available to inform their decision-making process. This could include operational data, performance metrics, customer feedback, etc

To enhance decision-making through data analytics, it's pivotal to grasp the variety of data produced by facilities, encompassing energy usage, maintenance logs, space utilization, and operational expenditure. Understanding this data aids in pattern identification, future issue prediction, and facility management optimization. It's also crucial to acquaint oneself with data sources and analysis tools like Building Management Systems (BMS) and Computerized Maintenance Management Systems (CMMS).

It comprehensively understanding this data, you can identify patterns, predict future issues, and optimize facility management. Familiarize yourself with the sources of this data and the tools used to collect and analyze it, such as building management systems (BMS) and computerized maintenance management systems

As a Monitoring and Evaluation/Data analyst, clarity in objectives is paramount. Defining goals ensures aligning with strategic priorities and also ensures impactful outcomes.

Data analytics is allowing decision takers in general to understand the dynamics of their business, anticipate operations needs and manage risks. It takes some measure of business to know which way will reveal the most useful information to be taken in consideration. That’s why predictive analytics takes data analysis a step further by forecasting future events or trends.

Trends reveal insights into data or information. This assists in planning and making the right decision to positively impact a program. activity or process.