What Does Data Engineering Look Like?
In the dynamic landscape of today's analytics and decision-making, having consistent and accurate data is vital. Comparable to the unseen plumbing in a building that ensures the smooth flow of water, data is the infrastructure that keeps the insights you depend on to stay ahead. Data Engineers are like the humble plumber, often overlooked until there is a catastrophic problem at which point they become invaluable. Doing basic maintenance on your plumbing can save you thousands of dollars and dramatically reduce future headaches, similarly investing in data engineers to keep your data clean and accurate will pay huge dividends in how fast you can respond to the ever evolving environment of today's business environment.
What Can Data Engineering Do For You?
1. Accessible and Available Data
Digital transformation, Artificial Intelligence, and Machine Learning all sound like a great idea on paper but can be difficult to translate into operational gains. So, what sets the successful programs apart from the majority that fail? Heaps and heaps of well structured, labeled, and correlated data. Data engineers are the ones that correlate, label, and verify data. They specialize in gathering, extracting, transforming, and loading data into structured storage in the effort to make information accessible and available. While this work can take a significant amount of time and often involves tedious tasks that require great attention to detail it is what sets the stage for advanced analytics that can truly push you to the next level.
2. Trust Your Data
For organizations to make data-driven decisions, trust in the underlying data is non-negotiable. Data engineers contribute to this trust by ensuring that data is clean, timely, consistent, and, above all, accurate. Working with SME’s in various processes data engineers are able to help ensure that the realities of the field translate to what your aggregate reports are actually saying. Enabling simple fixes, like enabling drop downs on a form, often yield to a disproportional increase in the quality of data and therefore the ability make solid decisions. Good data engineering will allow you to confidently make decisions that were once based only on gut feelings that may or may not be founded.
3. Let Your Data Talk
Data harmonization is the key to breaking down silos and increasing the efficiency of your organization. Data harmonization is a step above data integration, where both harmonization and integration gather data from various sources, harmonization then reorders the data according to a single schema allowing the information to be even more accessible than before. Data engineers use harmonized data to allow disparate sources to communicate seamlessly, providing a comprehensive and unified perspective. This process ensures that decisions are based on a holistic understanding, and a single source of truth.
4. As You Grow, So Will Your Data
Scaling operations require a robust infrastructure that not only keeps pace with current demands but is also flexible enough to support larger-scale endeavors. No one wants to have to fundamentally change their data structure because of an unforeseen business demand. By ensuring you systems are set up with data structures that are normalized with an eye to the future, data engineers play a pivotal role in the growth of your organization and minimize the effort required to upgrade systems when you do outgrow your current solutions.
5. Automatic Updates
The enemy of clean data is manual entry. Typos, poor training, seemingly meaningless fields and many other inherent traits of manual data entry can lead to a database that is unusable if it is not tended to by trained administrators. While no single tool can address all data engineering challenges, a data engineer's expertise lies in effectively collaborating with a range of systems and devising methods to facilitate seamless and automated communication among them. Data engineers can help devise a myriad of solutions to automate data collection where manual input is required and ensure that it is fool proof to enter correctly. By building pipelines to bring in quality source data, they ensure that any analysis and insights based on that data are based in reality, not the typos of an overworked technician.
In the ever-evolving landscape of data utilization, the role of data engineering is instrumental. It transforms raw information into a strategic asset, empowering your organization to make informed decisions. Additionally, it establishes a resilient foundation required to adapt to future technological advancements, ensuring you remain at the forefront of your industry.