After completing AWS Big Data training, the first step is to know how a Big Data architect’s life would be, job roles, responsibilities, and the skills that can be used properly. As a data architect, you need to understand cloud, databases, and relatable applications’ maximum potential.

It is not just one day, but every day of a Big data architect will be all about working with data modeling, conceptualizing, and database optimization. And an essential part is to understand that continuous education is needed to keep up in a big data architect career.

Major Data Architect skills:

  • Designing the data processing models for implementing the intended business model.
  • Developing the diagrams of the key data entities and the relationships between them.
  • Identifying the required components for building a designed system. 

Organizations used to build the architectures based on the appropriate standard format are known to be data warehouses. But today, the new technologies have altered the process of gathering information and serving their customers.

Businesses must predict their needs and the shift in the market for optimizing the outcomes and profits accordingly. When companies cannot upgrade their systems, the data will be dumped and decreased because of inefficiency. 

After completing the AWS Big Data training, a data architect will understand and maximize the data flow. The primary responsibility and daily work mode will be supporting the organization’s goals and providing a common language that people can use irrespective of the team. 

While creating an architecture design for processing the data, many points must be considered, such as security, data governance, and business philosophies. The data system architecture includes the operational data store that can help in business decisions. The main skills of a data architect are data modeling and database design. 

What is Data Modeling? 

The data model consists of numerous concepts such as data relationships, data constraints, and data semantics in an organized way. And most of the data models have the necessary operations for manipulating the data in databases. 

Data modeling is the first step in designing the best database. And it is considered that the database comprises relationships between the data items and the restrictions upon the data. A data modeling process will be like a formal presentation of the database structure. 

It is essential to identify the purpose of designing the database, such as where, how, and who will be using it. It should be simple because a complex one will be hard for people to utilize the data. 

The data modeling project will develop an inbuilt statement that is referred to during the design process. These statements will help in communicating with other people and keeps everyone on the same page. 

What is known as Data Base Design? 

While designing the database, two fundamental principles need to be considered. The reductant data equivalent to the wasteful data will increase the chance of inconsistency and business operations errors. 

And the other principle is about accuracy and the completeness of the data that will enhance the overall data efficiency. The reports made up based on insufficient data will lead to more damage to the business operations. 

While using a properly designed database will enable the teams to get accurate and updated information. Efficient database design will be the key to business success, and it also includes many other aspects. 

  • Eliminating the redundant data by dividing the available data into their respective subject-based tables 
  • Ensures the integrity and the accuracy of the included information
  • It supports the business data processing goals.

Few Pointers regarding the Enterprise Data Architecture

The data architecture model for an enterprise is a strategic design model that is the basic foundation of data usage for achieving business goals. And these models are specifically tailored for the organization’s respective operations that include metadata and data governance. 

And these specifications are based on six main key points that are listed below. And also, these have been taught during AWS Big Data training. 

  • Data sharing, data security, data governance, and data security
  • Handling the millions of data during real-time processing. 
  • Support the business philosophy for the sake of customers and clients. 
  • Shifting to predictive analytics when needed
  • Enhances the responsiveness to online users
  • Accomplishing the new data sources and new applications. 


Brief about Cloud-Based Data Lakes

The main aspect of the database architecture is integrating the cloud-based data lakes. And the Hybrid clouds are becoming popular for keeping up with the modern database warehouses. Data lakes will be storing different types of data types such as semi-structured, unstructured, and structured. 

What are the responsibilities of a Data Architect? 

It is quite clearly explained about the responsibilities during an AWS Big Data training. Typically, the training begins after graduating with computer science, IT, or any other similar degree certification. 

Hands-on experience can be gained while working in database administration or programming jobs. For becoming a perfect data architect, you need to achieve years of experience. One needs to have the knowledge and skills to get ahead of their career. 

You need to excel in RDBMS and SQL systems for a strong understanding of the topic. Other tools such as analytics platforms, Java and Python, ETL, Hadoop, Spark, Yarn, Kafka, and other tools are necessary. 

This is all about the day of a Big Data architect. All these roles and responsibilities are part of excelling the data architect job. And you can learn all these aspects and excel by attending AWS Big Data training. 

This training section has all the aspects needed to start your career as a Big Data architect. But remember you have to learn every step of your job to enhance your career.


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