Data Cleansing




Data cleansing, also known as data cleaning or data scrubbing, is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in a dataset. The goal of data cleansing is to improve the quality of the data and ensure that it is accurate, complete, and consistent. This is a labour intensive process and can take upto 70%-80% of any data science project.

Data cleansing involves several steps, including:

Data profiling: This involves analyzing the data to identify any inconsistencies, errors, or outliers.

Data standardization: This involves converting data into a consistent format or structure to ensure that it can be properly analyzed.

Data enrichment: This involves adding additional data to the dataset, such as geographic or demographic data, to enhance its value.

Data matching: This involves comparing data from different sources to identify duplicates or records that refer to the same entity.

Data validation: This involves checking the data for completeness, accuracy, and consistency.

Data transformation: This involves converting data from one format to another, such as converting text data to numerical data.

Data normalization: This involves scaling the data to a common range or distribution to make it easier to analyze.

The benefits of data cleansing include improved data quality, better decision-making, reduced errors and costs, and increased efficiency. Data cleansing is an essential part of data management and should be performed regularly to ensure that the data remains accurate and useful.

We have a pool of experienced Engineers and Managers. We take care of your Data Cleansing challenges. We setup your teams for you. Be it Project Consultancy, Agile Team Management, Software Testing, Machine Learning Models, Product Development or just simple software development. We provide A-Z of Data Science SDLC services, the complete package.

Having the working background from DevOps, Automation and as Solution Architect, we will streamline all your Data Science processes.

Our hourly rate ranges between $15 - $60 per hour for project based work.Our primary focus is all Data Science related areas namely AI, BI, Big Data and ML.

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