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Recent News: DNAMIC announced Number 1 of the Top Costa Rica Custom Software Developers by Clutch.co – Learn More Details
The Value of your Data
I’ve always wondered why most companies undermine the value of their data. When you think about it, your company’s data conceals the answer to what happened, your ability to accurately grasp what’s occurring right now and the possibility of forecasting the future. So, why would anyone ignore such a powerful source?
Building my own data services company and working with clients in challenging industries like health tech, finance and construction revealed a simple truth: We’re all buried in our businesses’ tangled intricacies and constraints. This truth is far more restricting than we frequently recognize.
Data has become an invaluable asset across various industries in recent years, and construction is no exception. The global construction industry, which generates trillions of dollars each year, is expanding rapidly. By 2020, 73% of U.S. contractors were utilizing building information modeling (BIM) in some form, with AI, robotics and 3D printing also gaining popularity.
Needless to say, at the heart of this transformation is data—specifically, how it’s stored, analyzed and leveraged to make projects more efficient, cost-effective and sustainable. At this level, data lakes, in particular, play an important role in this transition, assisting construction companies in managing massive and diversified datasets that standard SQL databases simply can’t handle.
One of the most significant advancements in data management has been the introduction of Delta Lake, which builds upon the flexibility of traditional data lakes while addressing key challenges like data reliability and performance. By using Delta Lake, construction companies can handle both batch and streaming data, ensuring data quality and consistency throughout project life cycles. This is particularly relevant for the construction industry, where a combination of structured and unstructured data is generated across multiple locations.
With Delta Lake, businesses gain the ability to perform real-time analytics on their data without worrying about data corruption or slow query performance. This system ensures that as new data is ingested—whether it’s from IoT devices monitoring equipment or drone footage surveying construction sites—it remains clean, consistent, and accessible for advanced analytics or machine learning models.
Construction projects are complex endeavors that generate massive amounts of data at every stage, from initial design and planning to procurement, project management and final delivery. Large-scale projects, such as data centers, hospitals, universities and stadiums, frequently span numerous areas and require complex logistics, labor management and budgeting. In 2023 alone, companies in North America secured billions of dollars in contracts for big construction projects such as international airports and data center projects.
These endeavors are large—thus, data management is crucial. Construction businesses handle structured and unstructured data. This includes project timelines, drawings and financials as well as drone footage, equipment sensor data and worker safety logs. Traditional data storage techniques often fail with this large amount of real-time data.
A standard SQL-based data architecture excels at managing structured data but struggles with unstructured or semi-structured data. Here’s where data lakes come into play. Data lakes enable organizations to store massive amounts of raw data in its original format, whether it’s structured (such as project schedules or financial reports), semi-structured (such as JSON files or XML documents) or unstructured (such as photos, video feeds or sensor data).
Data lakes provide flexibility. They don’t require predetermined schemas or classifications, which is ideal in construction, where new data sources may emerge mid-project. They also enable real-time analytics on data streams, which improves decision-making processes by revealing previously unavailable insights. For example, labor risk data from several locations can be combined in a data lake to help firms predict labor shortages or wage inflation.
Companies can use data lakes as a centralized repository to incorporate complex data analytics and machine learning models, transforming raw data into actionable insights. Predictive analytics is already transforming the building business. Companies can improve their labor, material and schedule decisions by examining previous project data, weather forecasts and real-time market conditions.
Predictive analytics can help organizations with tight deadlines adjust resources and timetables for labor shortages and adverse weather. This data can also help large construction businesses optimize resource allocation, labor management and project hazards across multiple locations. This is crucial in fluctuating labor markets or strong constraints that affect project costs and timelines.
In construction, inefficiencies at any level can cause delays and cost overruns. Data lakes enable real-time data streaming and continuous monitoring, allowing businesses to keep on top of project performance. Companies can automatically highlight issues like equipment downtime, labor shortages and safety compliance concerns as they develop, allowing project managers to take corrective action right away.
Furthermore, data lakes promote transparency among teams and stakeholders. By consolidating data into a centralized system, all project participants—contractors, suppliers and clients—have access to the same real-time information. This transparency accelerates decision-making and encourages a collaborative working environment, resulting in better project outcomes.
Sustainability is becoming a top focus in construction, and data is once again critical to meeting environmental, social and governance (ESG) goals. Companies can use data lakes to track and analyze large amounts of data on energy use, waste management and carbon emissions across multiple projects. Organizations may improve resource management and reduce their carbon footprint by incorporating IoT devices and sensors that monitor the environmental impact of building activities.
Despite all of the benefits, the transition to data lakes presents obstacles. Migrating from legacy systems to a data lake architecture may be difficult, particularly for large firms with multiple initiatives. During the transformation, it’s vital to integrate different data sources from several locations, ensure data quality and remain compliant with data privacy standards.
Additionally, personnel from multiple departments must be trained to handle and analyze lake infrastructure data. Data lakes are helpful when their data is readily available, but companies may lack the skills and tools to extract insights. Thus, choosing the right technical ecosystem for your company is one of the most crucial decisions you’ll make when planning for the next decades.
The construction industry’s data revolution is only getting started, but data lakes are quickly proving to be crucial tools for businesses wanting to stay competitive in a rapidly changing market. By centralizing disparate data sources and enabling real-time analytics, data lakes can provide construction organizations with the flexibility, scalability and insights they require to manage large-scale projects efficiently. As businesses globally adopt data-driven approaches, predictive analytics powered by data lakes are poised to become the norm for improving operational efficiency, mitigating project risks and advancing sustainability efforts.
Written on Forbes by
Arturo García is the CEO of DNAMIC – Specialists in Databricks Data Solutions.
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