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A data architect is responsible to create prototypes for data processing and maintenance systems. After analyzing the possible data sources of an organization; both internally and externally, architects develop a strategy to incorporate, centralize, secure, and preserve them.
We live in an agile world today where a Data Architect is the professional responsible for associating all a company’s IT properties and goals. Those talking about entering this profession should be well informed that this job involves not only dealing with data, technology, infrastructure, and cloud computing, as well as the ability to properly develop how the network and its elements fit with business needs.
The manner the development plan realizes the model in a regular activity is also important to recognize. It is not just about in-depth technological expertise; it is also about the willingness to use it in the sense of the range of business practices.
Qualifications of a Data Architect
The following are some of the most importantdata architect qualifications:
- Strong logical and strategic skills
- In-depth experience of usage of data, systems, methodology, architecture and modelling
- Outstanding communication and writing skills
- Ability to efficiently schedule and organize big data
- Know-how of distributed databases, processing, network management, performance management, as well as application architecture
- College or master’s degree in Computer Science, Math, or Stats
- Expertise on SQL Server, Oracle, or other DBs in different OS environments, like Linux, Unix, MS Windows, and Solaris
Is Data Architect Career Worth It
Data Architects aim to focus on the architecture and design. They work on the modelling of data for monitoring and reporting solutions. Since a data architect has to work with various application teams, it is assumed that this professional can thoroughly address the needs of customers from various industries to tailor the services to their requirements. In addition, highly qualified experts typically demonstrate in-depth engineering skills, particularly on topics and resources such as ETLs, BI, and SQL databases.
Data Architect Job Requirements
When hiring big data architects, enterprises are becoming more rigorous day in and day out. It got to the point that certain businesses want data architects who are the pros of using data modelling software. That is why data architects are often senior workers with several years of experience in business intelligence. Here are the most important job requirements of a data architect.
Diversity:
Firstly, a prospective applicant should be able to communicate and interact how big data pushes a company. Then, a data architect must be willing to deal with a wide range of extremely segmented systems with extremely diverse data.
Collaboration:
More specifically, a good data architect knows how to collaborate each or all of the: information technology data, development data, web traffic data, human resource data, financial data, geographically distributed data, customer loyalty data, all of which can be connected to its unique framework, programming language, and collection of instances.
Familiar with Tools and Technologies:
Possessing excellent skills in big data technologies and tools such as Hadoop, Accumulo, MapReduce, Panoply, Hive, MongoDB, Cassandra, and HBase, as well as data modelling and processing tools such as Oozie, Impala, Mahout, Flume, Sqoop, and ZooKeeper is of critical importance. Linux, Java, Python, and PHP provide related scripting language.
Technically Apt:
Eventually, some expertise in developing and managing broad on-premises and cloud-based DWH solutions using cluster and sequential RDMS and NoSQL architectures is appreciated by most businesses.
How to become a successful data architect?
A data architect should be able to comprehend and analyze market demands and then convert the data into concrete solutions for the system. This entails not only to be accountable for the locations of external data storage i.e., data centers, as well as the collection of data into repositories. It should be about preserving those repositories’ security and integrity.
One of the most crucial skills for data architects is leadership. It helps them to develop and report data standards when working to introduce, plan and manage ecosystem & database administration staff. In addition to designing and evaluating various database designs, data architects may also be able to oversee database architecture, data repository design, and models.
Technical expertise is beneficial, if not needed, as with most technology careers. Even so, data architects often need to be business-minded, and for this high-demand position, expertise in a related non-technical position could potentially improve your brand value.
Here are a few proven ways to become a Data Architect:
- Pursue a bachelor’s or master’s degree in computer science, math, computer engineering, stats, or a related field. Begin with a bachelor’s or master’s degree in science, or a similar area of computer engineering. Core curriculum must include data management, coding, big data creation, system development, as well as architecture of technology.
- Join an Online Bootcamp Program. Search and find a good and reputed online bootcamp program and learn from there. Many universities and websites are offering online bootcamp programs for students to learn and launch their career in Data.
- Polish and master your technical as well as business skills from data mining to critical thinking and problem solving. You can also find several books and programs that can help you develop your abilities. However, constantly looking for training to enhance the experience you have now and experiment with new problems is the key to improving successfully. Ask someone whether they can share any of their expertise with you if you know somebody who is currently employed in this area. On the off chance, you donot know the field expert, you can follow the blogs, or you can just log in and check for experts on LinkedIn or Twitter who are ready to share a few of their expertise with you.
- Enroll in the in-demand Data Science, Data Analysis, or Big Data Certifications Training Program. Another great way to take s tart is by enrolling yourself in a popular Data Science, Data Analysis, or Big Data certification training programs. You can easily find these programs online as many websites and companies are now offering training programs for both individuals and organizations for their development and growth.
