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In today’s digital era, data is the backbone of any organization, and the ability to manage it efficiently is critical to its success. Data processing is the process of extracting relevant information from various data sources and transforming it into an easily comprehensible format. It involves manipulating and processing data sets to transform, classify, interpret, or retrieve information that can be used across the business to plan, strategize, and forecast effectively.
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In today's digital era, data is the backbone of any organization, and the ability to manage it efficiently is critical to its success. Data processing is the process of extracting relevant information from various data sources and transforming it into an easily comprehensible format. It involves manipulating and processing data sets to transform, classify, interpret, or retrieve information that can be used across the business to plan, strategize, and forecast effectively.
Data processing comprises several key activities, including validating data sets, converting raw data into machine-readable formats, managing the storage, collection, transformation, and organization of data, and understanding user requirements of data. To succeed in data management, businesses need to hire quality data processing specialists who are up-to-date with recent data processing tools and have the necessary data interpretation skills while keeping employment costs low. One cost-effective solution is outsourcing.
Outsourcing data processing tasks to experienced professionals in the offshore environment can be highly cost-effective for businesses. Since the cost of living is lower in many offshore locations, businesses can outsource repetitive and time-consuming data processing tasks for a fraction of the price it would cost to hire specialists locally, up to 70% in some cases. Other benefits of outsourcing data processing services include:
Increased output efficiency and quality levels: Sending routine data processing tasks to an offshore team means your onshore team will have more time, budget, and project scope to take on higher-value work, resulting in a drastic increase in productivity levels within your data management services.
Business growth and scaling opportunities: Outsourcing time-consuming tasks to an offshore data processing team allows your local team to focus on increasing profits and business growth opportunities. The additional capacity from your offshore team's support means you can grow your business sustainably.
Various data processing roles can be outsourced to offshore teams, including data processing specialists, data entry specialists, data processing technicians, data entry clerks, data processors, and data analysts. These roles work closely with data visualization, order processing, and data analysis teams and form part of the data management function of the organization.
Depending on the volume and type of data to be processed, data processing teams are typically formed with a lead analyst, 1-3 data analysts (intermediate to senior level), 5-10 data entry specialists, one or two subject matter experts if necessary, and a quality assurance specialist. A company may need just one team unit to fulfill their needs, or if they're processing large amounts of data, they may require as many as 10 teams with a total of 100-200 staff members. Offshore data processing team leaders typically report to a local Chief Information Officer or a specific department manager.
Data is continuously changing, and outsourced data processing teams need to ensure that the information they handle is up-to-date and that any changes to the data are communicated. Cloud-based sharing systems provide a continuous flow of updated data at all times, no matter who changes what on each side. Data security and privacy can also be major concerns for businesses when outsourcing, and outsourcing providers place high emphasis on ensuring their security setup is up to scratch. Finally, since data processing is quite tedious and repetitive, it's important to keep your data processing team feeling like they are part of the "big picture" and communicate exactly what effects their data processing tasks will have on the project as a whole.