A look at how to provide informative and current real estate insights by centralising data within a data lake.
Data-driven insights are a necessity for all businesses, as making decisions based on estimates becomes a thing of the past. This is no different for asset managers.
Improving accessibility to data generated by real estate assets significantly influences portfolio performance. A key tool that asset managers can use when integrating technology is using a data lake.
Data lakes are helpful in streamlining workflows, highlighting listings, and using automation to consolidate leads. A data lake provides a centralised platform for all of an organisation’s information. Integrating a data lake is vital within real estate because asset managers need relevant information to remain in tune with the market and capitalise at the perfect moment.
Technology continues to integrate into every aspect of the real estate industry. The market must keep up to date with innovations to remain competitive. A company’s ability to make data-informed decisions is essential to reach profitability. But, even more important, is how well asset managers can adopt the right practises for effective data utilisation and fusion.
But what is a data lake?
Simply put, a data lake is a centralised repository that allows users to store all their structured and unstructured data. The lake holds the data in its ‘raw’ format. This is compared to a hierarchical data warehouse, which relies on files and folders to store data.
Think of it as a metaphorical lake of information, where inputs are free-flowing and come in a variety of formats. This makes it much easier to find data across a variety of regions. Instead of disparate and disjointed data across each pocket of the industry, data is centralised and accessible.
With artificial intelligence and automation developing so quickly, having all data accessible, easy to find, and malleable is fundamental to adopting the latest tools of automation. With constant updates, old formats of organisations can quickly go out of use.
Data lakes were created as an updated iteration of a data warehouse, meaning they were created to address the predecessor’s limitations. Offering a single, consolidated, repository of information, data lakes are the future of data-driven decision-making.
Why is a data lake important in real estate?
Data lakes are popular in every industry. They offer a scalable, accessible, and adaptable alternative to traditional data warehouses. In real estate, an industry flooded with quickly expiring data, they are game-changing.
Stonal’s web platform is a useful example of how data lakes can be deployed to help asset managers better manage their data. Stonal’s platform collects data from all sources, whether documents, plans, or from your ERP. The platform consolidates it into a single repository, providing immense benefits to asset managers who can use it to quickly compare against both internal and external data.
The data lake also helps integrate AI into real estate. With all the attention given to ChatGPT and the rise of AI, it’s hard to understand how exactly that will benefit real estate.
A centralised data lake allows managers of real estate assets to transform raw data into structured data through analytics, supported by AI. As mentioned earlier, with AI systems growing so rapidly, it’s risky to implement systems that rely on proprietary software. With a data lake, the information is flexible, meaning new AI systems and updates can operate seamlessly on your existing data platform.
Generative AI uses a data lake to function. AI is trained on data lakes to recover patterns and relationships, create rules and make judgments. If asset managers want to quickly update systems to have the latest technology, data lakes are fundamental.
Stonal’s platform centralises data, making it easily accessible and allowing applications of artificial intelligence to compare data across various sources. Stonal’s web platform is based on an architecture for consolidating and sharing real estate data.
Why is this transforming the real estate industry?
Data lakes are a necessary addition to the real estate industry as AI rapidly develops and becomes increasingly central to our decision-making process.
The traditional issues with data lakes are centred around some of the critical features associated with the format. No support for transactions, no enforcement of data quality, and poor optimisation.
One of the recurring risks of utilising a data lake for any organisation is security. Data lakes are difficult to secure and govern as they offer a form of free-floating data. There are solutions to this, such as a data lake house, which is a form of transactional storage layered on top.
Stonal’s platform addresses a key industry concern: security. Guaranteeing platform availability of 99.9%, the architecture implemented meets scalability requirements to ensure a high level of service.
Stonal’s development of its own data lake also reduces the risk of data replicates and offers a scalable solution. Addressing the problem of data quality and ensuring that the real estate industry is removing unclean data.
Don’t be sunk by making data-less decisions.