What is Data Sourcing? Type Process Tools Jobs Benefits Challenges and more

Data Sourcing
Data Sourcing

“Information is the most powerful weapon” This is the most suitable quote for Data Sourcing.

Data is just another form of information. The correct information is the crucial factor for the success of a Business.

Everyone needs information before starting any work or project.

Businesses putting serious money on Data Sourcing, Collection, and Information gathering, do you know why?

The information helps to decide the type and quality of the product that the customer loves to purchase.

Isn’t it cool to get paid just for collecting the data and converting it into a logical and meaningful format?

In this detailed article, I have covered everything about data sourcing you need to know about.

This article covers the process, tools, strategies, jobs, benefits, and challenges in data sourcing.

Let’s dive in                                      


What is Data Sourcing?

Basically, Data Sourcing is the process of data collection from the different sources for a specific target and to achieve a specific goal. This process is performed to know the target’s behavior and to deliver a better service to them. Data sourcing is a crucial part of successfully achieving business objectives.

Online and offline surveys are well-known examples of data sourcing.

Data Sourcing Benefits

There are multiple benefits of data sourcing from a business point of view. The benefits are as follows

  • Helps to make right decisions about investment and products
  • Helps to generate quality Leads
  • Improves Conversion rates and sales
  • Predicts market trend

Roll of the Internet in Data Sourcing

In this digitalized world the data plays the central character in the growth of a business. The term Business intelligence is all about the right and organized use of well-researched data.

Internet is the hub of data but to find the correct data it is important to be very precise and clear about the objectives you want to achieve.

Big Data is another term that most companies are using nowadays. Big data analytics represents a clear picture of every aspect of the business. The decision-makers of the business can make decisions on the basis of big data analytics.

The Internet made data sourcing and analysis super convenient. Businesses can reach out to their prospects and gather the data easily.

What is Information Sourcing?

As we discussed earlier, data is just another form of information.

Actually, Data is a raw and unorganized form of numbers, letters, and words that don’t carry any logical meaning.

Whereas information is the collective and organized form of a group of data, that carries a logical meaning.

Information sourcing is not a direct process. It is extracted from the data.

So the information is just a derivative of data.

Data Sourcing Examples

Data sourcing is everywhere, and it is performed at each level.

The examples given below will help to present a better and clear picture of data sourcing.

  • Governments collect data before preparing and launching any scheme. They collect data again post-launch of the scheme to measure the impact of the scheme and services.
  • Security agencies collect data from different sources to keep eye on terrorists and criminals to prevent malicious activities.
  • Business Organizations collect data from different internal and external sources like surveys and algorithms, to understand the interest and behavior of their customers.
  • Think Tanks and Magazines release their reports on the basis of data sourcing from different platforms.
  • Advertising agencies perform “Ads Retargeting” on the basis of data sourcing. Google is one of the biggest data sourcing platforms on the earth.

Data Provisioning

Data Provisioning is the ability to access the data from the source system to the target system without the interference of the data warehouse.

Data Provisioning
Data Provisioning

Basically, there are four techniques that are used for data provisioning

Real-Time Data Provisioning

Real-time data provisioning is performed by two tools SLT (System Landscape Transformation) and Replication Server.

The data is fetched by these tools from the source system and pasted to the target system in real-time.

Near Real-Time Data Provisioning

Two basic tools BODS (Business Objects Data Server) and Informatica are used to perform Near Real-Time Data Provisioning.

These tools can fetch both structured and unstructured data and can fine-tune it according to the requirement before pasting it to the target system.

Data Federation

This method is known as the smart data provisioning method. In this method, only meta-data is required to be pasted into the target system.

The actual data remains in the source system and the virtual data tables are created through meta-data into the target system.

Local Import of Data

Local import of data in the CSV and XLS format is also a method of data provisioning.

Data Sourcing Process and Strategy

Data sourcing is a complicated and multi-stage process. Therefore it is important to have a proper strategy in mind before starting this project.

Data Sourcing Process consists of following Strategies

  • Information Specifics
  • Fixed-Timeframe
  • Appropriate Method of Data Collection
  • Collect the Data
  • Data Analysis

Information Specifics

Before starting data sourcing it is important to address these questions in detail.

  • What details I need?
  • Which topics should I include?
  • What should be the data sample-size?
  • What I want to accomplish?
  • What questions should I ask?

These questions are crucial to be addressed before starting a data sourcing project.

Fixed Time-Frame

It is important to decide a time frame for the data collection. The data collected during a fixed time frame makes data analysis easy.

Appropriate Method of Data Collection

The method of data collection purely depends on the following factors

  • Type of Information you want to gather
  • Time-frame
  • The Platform you want to use
  • Budget you have fixed for the project

Some popular methods of data collection are given below.

  • Online and Offline Surveys
  • Online Traffic Tracking
  • Online tracking of transactions
  • Marketing Analytics Data
  • Monitoring Social media Traffic
  • Subscription and Registration based data collection
  • Offline Stores data collection

The method of data collection completely depends on the type of data you want to collect and the product you want to create.

Collect the Data

Now you can start collecting data once ready with your plan. Prepare a schedule and stick to it until a new situation arises.

Monitor your progress and update your schedule as per the present situation.

Data Analysis

Now it’s time to convert the raw data into useful information once you are done with your data collection.

This is a critical and crucial step and needs to be implemented carefully.

You can use the findings and patterns to improve your business revenue.

Data Sourcing Best Practices and Techniques

  • Desired Business outcome should dictate what data is required. The over-analysis of data can create confusion so let it be as simple as possible. In simple words “Try to gather the high-quality data based on the desired outcome of the business.”
  • The data you are going to source should meet your requirements. You data provider should have proper knowledge about your business and profile of data you want.
  • You should try to avoid the data prepared manually. Using manually prepared data may cause compromised data quality. Switch to the system extracted data because it is more reliable. Collecting data from the original source is always recommended.
  • Do not extract the unwanted data because it creates complexity and distraction. Fetch the useful data and leave remaining.
  • Always focus on data quality and set the required filters to get high-quality data. Set the standards to identify the data quality issues at initial stages.

Data Sourcing Challenges

Data sourcing is not an easy task. A business may face a lot of challenges during this process. A few of them are given below.

Data Sources Types and Providers

Basically, there are two types of data sources that are used to fetch the required data. From a business point of view, the data can only be fetched from two major sources.

File Data Source

Data is stored in a file format at a particular location. You just need to type the name of the file to fetch the data. It is the most convenient way to store the data.

Machine Data Source

The name indicates that the data is stored in the device in an encrypted format. The user having Data Source Name (DSN) can fetch the data only. This type of data source is not easily sharable but can be fetched with the right data source name.

Data Providers

The data provider and management companies are growing very fast. This is happening because the demand for data is exponentially increasing.

High data quality should be the top priority of businesses. A good data provider cares about the requirement, correct structure, and quality of data.

Data Sourcing in Business Intelligence

Data sourcing can revolutionize business growth by providing a clear vision about the behavior, needs, interests, and background of the customer.

Business Intelligence is nothing but “Knowing about prospect’s behavior, interest, and needs based on gathered information from different sources before creating a product.”

Sourcing data to solve a Business problem

Most businesses undermine the role of data sourcing in their business growth. Data sourcing not only helps to improve the business but can solve major business problems.

The data patterns and analytics gained by data sourcing have the capability to guide a business in the right direction.

The insights created through the analysis of raw data may represent the actual customer behavior, product quality and quantity, market trends, and right product decisions. The branding and marketing problem of business can also be solved through the right data collection method.

Data Sourcing Companies

Data sourcing shares a huge market chunk of $64 Billion in 2021 and aimed to be $103 Billion in 2027 (According to Statista).

Big Data Market Size
Big Data Market Size

There are many big and small players in this field. A list of companies is given below.

And a lot of others.

Data Sourcing Jobs and Responsibilities

Data sourcing and Data Science is an evergreen Industry. Companies hire professionals in this field for different job responsibilities.

Based on the responsibility the companies offer different posts for this job. The posts are given below.

  • Marketing Executive
  • EPF
  • ESIC
  • Database
  • Lead Generation
  • MIS
  • Survey Supervisor

You just need to check out the notifications published by companies on the regular basis.

Now check the eligibility criteria and fill-up the form if eligible.

Companies pay well to their data source employees.


Data Sourcing plays a pivotal role in the ecosystem of a company. The insights generated through correct raw data can significantly affect the growth of the business.

Businesses shouldn’t undermine the role of data collection and should focus on the quality of the data.c

The whole process of data sourcing is critical for a business because it is the basis of the right product creation.

The data provider should be credible and businesses should avoid manual data. Data collected directly from the source is always recommended.