Data Engineering

Data engineering is creating storage vaults to reserve a vast amount of data.

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What is Data Engineering?

It is the process of developing and building systems to facilitate data storage. Data engineering supports functions like data analytics, business intelligence, and machine learning by providing required information. The process starts with collecting data from various primary and secondary sources, along with real-time information. Then next the experts clean the data by removing any errors and duplicacies. Databases, warehouses, and data lakes are some systems to store the collected information. Finally, data engineers ascertain the quality of data by conducting regular audits and monitoring.

analytics Workflow

Challenges and Capabilities of Data Engineering

  • Collaboration : Data engineering enables collaboration within the organization. Having stored information in one place means that new employees can go through the company's details without any hassle. Comprehensive documentation allows availability of data for all the employees, thus encouraging better collaboration.
  • Real-Time Data Processing:The requirement for real-time forecasting and analysis has become a need for many businesses. That is why data engineers are building data storage systems that process streaming data efficiently. This allows businesses to discover the latest insights and take timely actions.
  • Complex data integration:Businesses collect data from various sources like APIs, Excel sheets, IoT devices, and external partners. All this information is in different formats, schemas, and naming conventions, which makes it difficult to integrate it into one platform. The solution is to put data in a similar format, build stable pipelines for smooth transfer of information, and handle errors in a timely manner.

Applications of Data Engineering

Data engineering builds robust pipelines and infrastructure to process, clean, and organize data for analytics and AI.

  • Agriculture: The most recent technological advancements are positively transforming the agriculture industry. High-tech tools like drones and sensors collect data on moisture, nutrient levels, and pH in soil. This makes it easier to understand soil moisture content and plant health. Data engineers further design real-time harvest data processing systems to make predictions based on information collected. This aids farmers in determining when fertilizer and irrigation are required.
  • Retail:Data engineers store valuable data such as product sales and supplier stock levels. This data provides insight into the sales numbers of each product. This helps retailers optimize their stock levels accordingly, reducing overstocking, understocking, and minimizing storage costs.
  • Finance: Banks need to submit their regulatory reports on financial health and loans to higher authorities. So banking institutions need to keep their data updated to prepare reports that are timely and accurate. Data engineers build pipelines that help transfer transactions, loans, customer accounts, transactions, and compliance into one place. By doing this, data stays updated and easily accessible.
  • Telecommunications: A CDR (customer detailed record) is created each time a customer contacts or receives a call, sends or receives an SMS, or uses mobile data. Data engineers must process the millions of CDRs that are created every day as fast as possible.They do this by creating reliable data storage solutions.
Business Applications

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