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Will Data Cleaning Be a New Sector For Tech Companies

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Will Data Cleaning Be a New Sector For Tech Companies

It won’t be an exaggeration to term data as soul of present technological world. Increased use of technology creates a massive amount of data from various sources viz. Cloud, web, mobile, IoT and others. These data contains vital information that can be used for various purposes including but not limited to generating business insights, formation of strategies, enhancing performance and research. Modern advance technologies like Artificial Intelligence (AI), Augmented Reality and Virtual Reality have data management and analysis in their core. It’s worth mentioning Data as present and future of world. Everyone must have heard of lost jobs due to application of modern technology, but can’t deny the fact that new technology always offer new job opportunities. It applies in the sector of data analysis and management too. Humans are required for data cleaning which is now an emerging sector for tech companies.

What is Data Cleaning?

With Data scientists or Data analyst being highly paid jobs, many new “Big Data” companies, Data analysis software, Data visualization tools and other products have been emerged in market. But, if the input data is not cleaned or managed, all these products are useless. Data cleaning is term for all the process and steps involved in transforming generated data in usable and machine understandable format. 80% of total data analysis task involves data cleaning that makes it an essential work for going further. Data Cleaning: New Job generating sector Raw data, collected from various sources, can be of several categories, corrupt or hard-to-understand formats. It’s a need of every business users to have solution that can provide easy and quickly cleaned data for enriching data capabilities, reducing error, eliminating noises and better insights. A company can’t provide similar approaches for all type of data, it requires manpower to clean out and sort utilizable data as we have not reached at that higher level of technological advancement. Here are some of the job opportunities in this sector: Self Service Data Cleaning: Every business have specific data requirement to produce useful insights that can enhance the business performance. For meeting the needs, people with expertise in specific sectors are hired for their data cleaning. He must know what data should look like for data cleaning. It’s a laborious task that requires certain set of skills and knowledge that are discussed in next section.

Data Formatting and filtering:

Due to vast category of generated data, Data formatter will transform raw data into machine or system understandable and processable formats. Take an instance when raw data is in form of video, audio or graphics, it need to be properly formatted in digital form for producing required insights. Noise Cleaner: Raw data can have many error or noises that can harm all the set. Noise Cleaner specifically works for eliminating such kind of data to prevent further functioning. Essential Requirements for a Data Cleansing Job: For grasping data cleansing job, one should have knowledge of basic languages that are being used for Data Management and analysis like Python, R, SAAS, SQL etc. He has to perform following types of tasks:

1. Import & export of data sets 2. Naming or renaming variables 3. Changing the type of variables (also known as explicit coercion) 4. Sorting on one or more variables, with duplicate keys or entire duplicate records 5. Selecting columns from input data set to output data set 6. Filtering of rows based on one or more conditions 7. Creating new variables through functions of existing of variables 8. Conditional processing of variables (i.e the values of new variable is based on the values of existing variables) 9. Appending tables 10. Joining tables (Inner Join, Left and Right Join, Full Outer Join) 11. Transpose tables 12. Summarize column or summarize column by groups 13. Normalizing and standardizing columns (for continuous variables) 14. Binning of continuous variables 15. Imputing missing values in a variables

There are many other tasks that are required for unstructured data. Summing up, it can be said that Data is at the core of digital transformation and Data Cleansing is essential step for “Big Data” analysis and management that require high manpower. This new sector can create a plenty of jobs and new opportunities for tech companies.

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