You're a commercial real estate professional. How can you make sure your data is accurate?

This is a great question, and the answer will depend on how your local municipality and/or state allows property sales information to be shared. Is it public or not? If so, a broker can build their database based on readily available public information. This is the case in Kentucky. Two important mentions: 1. Never really ONLY on third-party reports (like CoStar, etc.) as they will by nature have missing information. 2. Site your sources. If you are building a market report for your clients/community, cite the sources you are using for the data you are interpreting.

Verify property information through reputable sources, cross-reference data with public records, and conduct on-site inspections. Regularly update databases, leverage advanced technology for data validation, and establish communication channels with reliable industry contacts. Implement robust quality control measures to ensure accurate and up-to-date commercial real estate data.

I apply two methods: 1-Apply some quick broad logical tests. E.g. divide total revenue by lettable e area to come with rate. If it is within expected range fine, if not requires digging in. 2- Random sampling. Take a small number of specific transactions or reports to look at them. If something major is off, it will most likely show up.

Unlock market intelligence with good data! Gather info yourself (primary data gathering) (think traffic counts, surveys) for precise insights, but it takes effort. Leverage pre-built data like 3rd party reports for faster access, but the data may be skewed for other purposes. Choose wisely: Combine both for a powerful mix! But remember, pre-built data can have biases. Understand how it's collected and by whom. Trustworthy sources are key! Data = Potential: Don't just collect, analyze! Ask: what does it reveal, is it reliable, and how does it help my goals? Finally, don’t get stuck with “analysis paralysis” by over-analyzing and not taking action. Master data sources & analysis, and unlock informed decisions for your business success!

Additionally, consider noting the data collection methods employed, whether automated or manual. Highlight any data transformations or preprocessing steps undertaken before integration. Acknowledge potential biases or uncertainties in each source and detail any validation procedures in place. Understanding the context of data generation and potential limitations aids in establishing a robust framework for maintaining accuracy and reliability in your data management strategy. Regularly updating this documentation ensures adaptability to evolving data landscapes.

In my experience the results will only be as good as the data. Since we have so much data out there these days, verification is of the utmost importance. I use highly qualified, well paid and accurate people to help with data collection and gathering. This allows me to know, beyond a shadow of a doubt if the data is reasonable. Then I also often will scatter plot, outliers are then scrutinized and removed if they are not representative of the market.

Independent verification is nearly always necessary. If you don’t understand the motivations of the parties reliance is suspect.

There are multiple data sources we rely on to compare data, but each has their own strengths and weaknesses and vary in strength based on market and product type.

You want to invest in quality data sources. The foundation of accurate data lies in where and how you're sourcing it -- it needs to be accurate and reliable. Utilize reputable data providers known for their precision and reliability in the CRE industry. This could be market research firms, established real estate analytics platforms, or government and industry reports.

Communicate your data properly Analyze your data and double check before sharing with someone . If possible try to communicate directly with property owner to avoid missmanagment of data . we Generally fill form to avoid such type ofinconsistency, or incompleteness of data.

Validating the raw data is the ultimate differentiator between a market participant and a market dominator. As a broker, you should select your niche, whether it’s an asset class or territory. By speaking to every buyer and seller in your market, you will be able to validate the raw market data and explain every comparable in your market.

Most Data input can vague. Research what your use purpose is, and research for accurate use. Then put you tools and knowledge to good use. Good luck with your research.

In addition to the mentioned methods, consider implementing data profiling techniques to understand data distributions and patterns. Utilize outlier detection algorithms to identify unusual data points that may skew analysis. Conduct regression analysis to assess relationships between variables and uncover potential inconsistencies. Collaborate with domain experts to gain insights into industry-specific nuances and validate data against real-world scenarios. Regularly update and maintain a comprehensive data dictionary to ensure consistent understanding and usage across teams. Employ version control for datasets to track changes and maintain data integrity.

understanding how data gets collected, coverage, info on terms used in the data also important. simple example would in office absorption, there is gross and net absorption, knowing which one was cited in any reports would make a difference on how Important that data input is. -always cross check any data given, from multiple sources for it's accuracy

Implemento rigurosos procesos de validación de entradas de datos. Verifico cuidadosamente la información recibida, corrigiendo posibles errores y confirmando la coherencia de los detalles proporcionados antes de incorporarlos a mi base de datos.

Regularly check the accuracy of the data you receive. Cross-reference information from different sources to ensure consistency. Leverage AI algorithms to identify anomalies or outliers in your data, and utilize the LinkedIn community to validate specific details or market trends.

Maintaining data accuracy in CRE is an ongoing process, crucial for keeping the data relevant and trustworthy. Regular reviews and updates are essential to ensure your data aligns with current market conditions and property specifics. This process includes: 1. Eliminating data redundancies to avoid skewed analyses, which could lead to incorrect conclusions 2. Correcting errors from manual entry, or system faults, or incorrect info from data sources 3. Filling in data gaps for a complete and accurate dataset. Each step is vital for preserving the integrity and usefulness of your data, supporting reliable decision-making.

Regular data cleansing is essential for maintaining data integrity. In addition to using data cleansing software, implementing periodic manual reviews ensures accuracy. Establishing a systematic schedule for updates, corrections, and deletions aligns with effective data governance. Integrate user feedback mechanisms to enhance data accuracy, reflecting real-world changes promptly. Collaborate across departments to address evolving business needs and ensure data relevance. This proactive approach not only sustains data quality but also promotes a culture of accountability within the organization.

To ensure accurate commercial real estate data, regularly update property information, cross-verify details from reliable sources, employ data validation techniques, and leverage technology for real-time monitoring. Regular audits and collaboration with reputable data providers also enhance accuracy.

Use reliable sources and cross verify or fill in any gaps with whoever agreed the deal in the first place wherever possible.

As a commercial real estate (CRE) professional, the most effective method to maintain data integrity is by staying actively engaged in the market. The frequency of your deals and interactions with people directly influences the quality of your data. Regularly reviewing and refining your data is essential. I personally establish daily tasks dedicated to reviewing properties, companies, and decision-makers to ensure my data remains accurate and up-to-date.

Regularly review and clean your data to eliminate errors, duplicates, or outdated information. AI-powered tools can help automate this process by flagging inconsistencies, and the LinkedIn community can provide real-time insights to verify the accuracy of specific data points.

São necessárias medidas de seguranças constantes. Como atualização de senha, limpeza de arquivos e verificação constante de qualquer detalhe diferente do habitual.

Maintaining pristine data in commercial real estate is akin to keeping a polished storefront – it enhances the overall appeal and functionality. I consistently prioritize the cleanliness of my data through regular reviews and rigorous quality checks. Think of it as dusting off the shelves to reveal the true value of each piece. By identifying and rectifying inaccuracies promptly, I ensure that the information is not just present but accurate, creating a foundation as solid as a well-maintained property. Remember, in the world of data, cleanliness is not just a virtue; it's the secret sauce for optimal decision-making.

from Data & analytical platforms in India, they frequently update to their quarterly absorption, sales, supply and other key metrics, this is to provide better accuracy citing to any over/under reportings. always make sure referral data is upto dated

Data is absolutely useful however firstly it’s understanding where it’s from and secondly, far more importantly it’s important to try and put the information into context. The key here is data by nature is at very best live or far more likely in property terms historic. What does this mean for the future? How will the data in your opinion look 12,24 months from now? That’s the key

Data is absolutely useful however firstly it’s understanding where it’s from and secondly, far more importantly it’s important to try and put the information into context. The key here is data by nature is at very best live or far more likely in property terms historic. What does this mean for the future? How will the data in your opinion look 12,24 months from now? That’s the key

If something seems wonky on the output — it probably is. With enough experience, you should be able to identify when data doesn’t look right and go back to the source to figure out what the problem is.

Utilize advanced analytics and AI algorithms to extract meaningful insights from your data. Understand the limitations of your data and account for potential biases. Cross-analyze data from different periods to identify trends and patterns, allowing you to make informed decisions.

To ensure meaningful insights, analyze commercial real estate data judiciously. Consider the context, purpose, and limitations of your analysis. Understanding the nuances of data analysis enhances the value of your insights.

Using the right tools for data analysis and visualization is a critical need. Real Estate professionals should adopt the use of even the basic Excel functions to provide insights that are actionable. But there are more advanced tools for big data like Tableau that can help create even more extensive analytics for decision-makers.

É necessario total transparência sobre os dados apresentados, tanto em relação ao clientes quanto aos proprietarios ou envolvidos diretamente. Pois as informações de forma clara e objetiva torna o negócio mais confiável.

Para asegurar la precisión de mis datos me esfuerzo por comunicar la información de manera clara y detallada. Utilizo informes transparentes y documentos fácilmente comprensibles, lo que facilita la interpretación correcta de los datos por parte de todas las partes involucradas.

Present your findings in a clear and understandable format. Use visualizations such as charts, graphs, and maps to convey complex information. Clearly articulate the sources and methodology used to derive your conclusions. Engage with the LinkedIn community to discuss your findings and gather additional perspectives.

Effectively communicating data to loan brokers, clients, and lenders is crucial for successful transactions. "Unlocking the potential of your data is like orchestrating a symphony – it requires precision, coordination, and a touch of finesse. For loan brokers, present your findings in a concise yet comprehensive manner, akin to offering them a curated roadmap to financial success. With clients, weave a narrative around the data, turning numbers into a compelling story. Think of it as painting a vivid picture of opportunities and risks, ensuring they see the masterpiece your data unveils. Now, with lenders, it's all about speaking their language – providing them with the hard facts backed by solid data. l

“Clear, concise and consistent” may sound good but may present instant red flags. Data can be consistently wrong. Practice does not make perfect. Bad practices make imperfect, inaccurate and incomplete. Artificial inflation and manipulation of data over time can reflect an upward trend and upward trajectory. However, the corruption is at the source — the bad actors. Huge banks have proven to be victims of multi-billionaire frauds. Commercial buildings have been lost over a gambling weekend. Exercise prudence. Be on the ground and check rigorously at source prior to making any big acquisition or move.

Ensure that title and deed documents are processed accurately and efficiently. Cleansing data collected from Multi Listing Sites (MLS) Cleanse data collected from MLS to ensure that it is accurate and up-to-date. Check government and public records to ensure that the data is accurate and up-to-date. Choose the right APIs to ensure that the data is accurate and up-to-date. Outsource real estate data management to ensure that the data is accurate and up-to-date. In addition to these tips, it's important to have a modern data governance framework in place to ensure that data is accurate and reliable. This involves implementing strategies to maintain the integrity and accuracy of data, thereby ensuring that analyses and conclusions are sound.

Stay updated on industry trends and advancements in AI technologies to enhance your data accuracy processes. Foster relationships within the LinkedIn community to access real-time market insights and validate data points. Regularly review and update your data governance policies to adapt to changing data landscape and compliance requirements.

es fundamental tener en cuenta: 1. Verificar la autenticidad de la información mediante fuentes confiables. 2. Implementar procesos de validación de datos para corregir posibles errores. 3. Utilizar sistemas actualizados y tecnologías que minimicen la probabilidad de inexactitudes. 4. Comunicar la información de manera clara y transparente para evitar malentendidos. 5. Mantener una constante actualización de datos a través de análisis de mercado y registros actualizados.