Business intelligence (BI) consists of different plannings used by organizations to analyze the data of the business.BI applied knowledge provides the business with the present, current and futuristic perspective of your business. BI deals with a large amount of data to create new strategies and work to grab better business opportunities.
Business intelligence improves the decision process of the organization and makes the organization working better and smoothly. BI takes its specific types as Mobile BI and Cloud BI which are in the current trend to draw insights from users and predict market behavior.
Mobile BI refers to the availability of customer datasets and access to use this information for better customer satisfaction via mobile devices. Mobile phones can be seen in every nook and corner and every interaction of users with various applications yields us a large amount of information that can be used to point out the market trend and customer needs.
Kindly fill below information
Investing in a property does not consider the past value but is keen to know about the future of the property and its potential value to grow at times of market fluctuations. And Customer Real Estate (CRE) is a sector that contains an abundance of data and studies every data which is being generated to predict the outcomes is what is not under the scope of humans.
Using Advanced Analytics Mechanisms, Predictive modeling was applied to the CRE data to predict the Vacancy in the specified region/market. It uses the past and presents big data to make reliable, proof-based predictions about the future development of a property.
Over the past years, analytics are slowly taking over its role among varied listing sites. Its chief role is to produce each consumer and sellers a lot of context regarding the property and its qualities. However, analytics that basically profits CRE agents continues to be a rare factor to seek out. and Hvantage provides you sophisticated analytics using various visualization and predictive modeling tools to uplift your business strategies.
Area | - | Machine Learning, Analytics, BI |
Language | - | Python 3.x |
Business Area | - | Commercial Real Estate, Finance |
Libraries | - | matplotlib, NumPy,pandas,seaborn,sci-kit-learn,h20,statsmodels |
Visualization Tool | - | Power BI |
Every business is associated with some degree of economic forecast, most frequently implicit. That is, value predictions for the business and current market are absent, however, the business leaders have an idea in their heads concerning the longer term. The human brain tends to grant massive stress to data that supports a person’s existing views, and therefore the brain dismisses contrary proof. Psychologists decide this as confirmation bias.
Understanding how the outside world impacts the market and business is best done through an economic dashboard. Hvantage provides you with an interactive dashboard comparing Fundamentals data (vacancy, rent growth, inventory). It supports decision-making and innovative problem-solving for business units in commercial real estate.
Leading the complete lifecycle of visual analytical applications from the development of mock-ups and storyboards to the complete production-ready application using Power BI, It also develops an entire pipeline from mining the raw data from BOX, Blob Storage to visualize it in Power BI using Azure Data Factory. It uses Databricks to perform-processing of data before visualization.
Area | - | BI, Analytics |
Language | - | Python 3.x |
Business Area | - | Economics Data |
Libraries | - | Numpy, pandas |
Tools | - | Power BI, Databricks, Azure Data Factory, Blob Storage |
Organizations want serious mechanisms to form, manage, share, and analyze abstraction knowledge. There are many elements, mobile and desktop applications, and developer tools. The obstacle is to supply the organization with a platform that may be deployed on-premise or within the cloud. Also adding graphics to a graphics layer is a straightforward show of little quantities of temporary geographic knowledge on a map however if we'd like to touch upon larger amounts of information even quite one thoHong Kongnd, then mercantilism knowledge and adding it to be map becomes troublesome.
Using ArcGIS geographic information system we created a web map and web map application. We extract the data from the cloud, database, and local machine and analyze the mapped information and managing geographic information from a database. We prepared a PythonAPI which is used to dynamically update the web map, web map application of the Arcgis online whenever we made any changes in the data. We created a web map application for sharing our map. We created three PythonAPI for Updating map which provides low latency:
Area | - | BI, Analytics |
Language | - | Python 3.x |
Business Area | - | In-House Research and Implementation |
Libraries | - | Numpy, pandas, ArcGIS |
Tools | - | ArcGIS Online |
Investing in real estate business involves a large amount of risk and queries which bothers the customers and forces them to have second thoughts on various decisions. Customer queries involve property location , bank loans, rate of interest, tax etc. Data insights and regular updates of data set provide a clear picture to customers and therefore there is a need for a system to manage financial insights of data generated.
Hvantage data scientist team and machine learning experts provides you with a system of gathering data to provide insights to drive decisions for people and companies using Data Science. Using Machine Learning techniques, the system is designed to deliver key points of interest and answer crucial questions relating to the Commercial Real Estate like the population sentiment of the current household, the likelihood of relocating, the pattern of new home sales & mortgages, etc. The system is trained to take constraints/parameters from the user as input and provide high accuracy predictions.
Area | - | Machine Learning |
Language | - | Python 3.x, Haskel (in future for general entity extraction) |
Business Area | - | Commercial Real Estate, Finance |
Libraries | - | matplotlib,numpy,pandas,seaborn,scikit-learn,h2o,statsmodels |
Visualization | - | Power BI |
Tool | - | ... |
The efficient flow of data from one location to the other i.e. from a SaaS application to a data warehouse is very important as large amounts of data insights are generated so as to increase the efficiency of your business. Data flow can cause a problem due to various issues like data can become corrupted, or data generation points may conflict and cause redundancy. As the requirements become more complex, the number of data sets increases and these problems impact scaling.
Also managing workflow along with directing data is often a difficult task. It requires you to see the essential outlines while simultaneously paying attention to the various minor details.
Using the latest technologies, Our Business Intelligence team has developed task scheduling and workflow automation systems with more flexibility, robustness, logging, and cost-effectiveness. Apache Airflow, an open-source workflow automation tool is being used to develop complex workflows having triggers and Acyclic Directed Graphs. Azure Data Factory is used to effectively enable data transport/transfer capabilities along with complex schedules of tasks.
Area | - | DevOps,ETL,Automation,BI |
Language | - | Python 3.x |
Framework | - | Flask |
Cloud Infrastructure | - | GCP, Azure, Heroku |
Business Area | - | Inhouse Implementation |
Libraries | - | Numpy, pandas, scikit-learn |
Visualization Tools | - | Power BI |
Libraries | - | Numpy, pandas, scikit-learn |
Tools | - | Apache Airflow, Google Composer, Azure Data Factory |
You can hire a single developer or any number of dedicated developers from our pool of 65+ expert coders. We have 3 unique hiring models designed according to your precise needs on the basis of time. These models are available part-time, full time, or on an hourly basis. Those who wish to hire our developers for their world-class business project can choose any of the three options according to their needs and preferences.