Machine Learning and Business Analytics have gained technological interest over the years. One of the important aspects of machine learning and business analytics, yet often overlooked, is data preparation. One of the major challenges of data preparation is that it is a time consuming process, along with needing consistent effort to shape the data and make it valuable.

Verde Tech Systems focuses to change the stride of data preparation and fundamentally prepare clean understandable data. Taking that goal into consideration, Verde Tech Systems uses various data wrangling technologies that are suitable to serve this purpose. One of our expertise is Azure Machine Learning Workbench, which includes powerful data wrangling capabilities using productive data transformations, to prepare the data.

Along with Azure ML, Verde Tech Systems has acquired expertise in Azure Data Factory Services and Azure Data Lake Solutions. Our experts use Azure Data Factory services as their architecture framework, comprised of a component called dataflows that is easy to setup, use and build lightweight data processing pipelines. We also provide Azure Data Lake solutions and another aspect of data preparation within the data lake ecosystem: data ingestion. Data ingestion is a form of data wrangling that performs some level of sanitization on the data (structured and unstructured) and prepares the data before it is sent to the data lakes and used for reporting, analytics and predictive modeling purposes.

Lastly, Verde Tech Systems has extended their knowledge of data wrangling by schooling ourselves with the top data wrangling tool – Trifacta Wrangler. Our teams have gained expertise in the Trifacta Wrangler platform as the tool has proven to provide accurate and efficient data that is adaptable to different data sources, organizes and structures the data as soon as the dataset is imported in the tool, provides smart suggestions and processes the results suitable for data analytics and machine learning tools.