It also requires acquiring specific technical skills and years of work experience before it can be mastered. If you wish to pursue a career in technology and you are good at analysis and organizing data, you should consider becoming a data architect.
Data Architecture is the process and design of information flowinan organisation. It also sets and implements the standards, protocols and rules required to control and deliver the information. Data modelling, database design and database administration are constituents of data architecture.
Data architects are as business oriented as they are with technology since they understand the businesses’ need to make decisions and how those decisions are based on data. It is the job of a data architect to ensure information is available at the right time at the right place so a correct business decision can be made.
Data architectureand enterprise architecture may sound similar,and while they both are intended to bridge the gap between business and technology, they are in fact vastly different in their purposes and scope. Data architects, through their job answer the questions – what, how and where the information flows. Enterprise architecture besides answering these questions also delves into the – who, when and whys. In short, data architecture is in many ways a subset of enterprise architecture.
The best path to follow in order to become a data architect is to pursue a bachelor’s degree in computer science, computer engineering or information technology. To pursue these courses, one must have Mathematics, Physics and Chemistry as their major subjects in high school.
A Bachelor’s degree is sufficient to get entry level data architecture jobs. However,employers prefer a master’s degree holder when considering promotions to senior roles within the same field. Data architects with technical certifications like Certified Data Management Professional (CDMP) help professionals stand out to prospective employers. Following are some of the other certifications available for data architects:
Cloudera Certified Professional (CCP): Data Engineer, IBM Certified Data Architect, Microsoft Certified Solutions Expert (MCSE), MongoDB Certified DBA Associate, Oracle Business Intelligence Foundation Suite 11 Certified Implementation Specialist, SAS Certified Big Data Professional, Stanford Data Mining and Applications Graduate Certificate. The US is the best country to pursue programs in Computer Science. Most IVY universities offer Bachelors and Masters level courses in Computer studies. The California Institute of Technology (Caltech) has a 4 years BS in Computer Science program. The University of Illinois at Urbana-Champaign (UIUC) offers a Computer Engineering program. The Georgia Institute of Technology (Georgia Tech) has a course in Bachelor of Science in Computational Media and also a course in Bachelor of Science in Computer Science.
In the UK, University of Cambridge has a 3 years Bachelor’s program in Computer Science. Imperial College London also has a B Eng. course in Computing. The University of Warwick offers courses in Computer science combined with Business Studies and Management Science. The Indian Institute of Technology – Bombay, Delhi, Kharagpur, Kanpur, Madras and Roorkeeare some of the top colleges in India that offer 4 years B Tech in Computer Science and Engineering courses. Birla Institute of Technology and Science-Pilani and Delhi Technological University are some of the other top colleges which offer a computer science undergraduate program.
Duration: 4 Years
Fee per course/annum: ₹ Rs. 800,000 – 1,400,000
Data Architects have only been there since the 90s but with data as the key to business decision making, their demand has only increased over the years. With time, the job of a data architect has also become more complex. They now use new technologies on existing databases to create low cost, secure and flexible data infrastructures.Some of the other responsibilities of data architects include collaborating with team members to devise strategies that address industry needs, building data inventory to implement the architecture, researching for new data acquisition opportunities, identifying and evaluatingexisting data management technologies, creating and developing data models for database structures, integrating technical functionalities in the structure, and monitoring quality and enforcing development standards.
Some of the top industries that employ data architects are:
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Whatever be the level of education, aspiring data architects must have knowledge of the data science technologies including R, Python, SQL, Hadoop and Tableau. Other must-have areas of knowledge for success in this field are application server software (like Oracle), user interface and query software like IBM DB2, XML, agile methodologies, ERP implementation, predictive modelling, NLP and text analysis, data modelling tools (like ERWIN, Enterprise Architect and Visio), data mining, UML, ETL tools, machine learning and data visualization.
Some of the most common job profiles for data architects are:.
The top companies which have hired data architects in the past include:
San Francisco in the USA is the best-paying city for data architects. On an average, data architects in the San Francisco area make $12,000 a month. Boston and New York are the other top cities in the US for a career in data architecture. However, most data architects in the rest of US make an average of $8,400 a month. The salaries of data architects in India is much higher in comparison to the other popular careers and ranges from Rs.80,000 to Rs.250,000 per month. In terms of pay, Bengaluru is the best city in India for data architects.
To become successful in the profession, you will require a combination of technical and interpersonal skills. Key skills in communication, organizational, creativity, innovation, multi-tasking, leadership and the ability work under pressure must compliment the technical qualifications you acquire over several years of studies.
A senior architect at PayPal, ArunaSusarla has over 15 years of data architecture industry work experience. She is credited with building high performance, innovative and scalable solutions for PayPal which have been deployed on mobile, and on Point of Sale retail systems.
A Big Data Architect at IBM in the Silicon Valley, Linda Liu does development work. She has a blog on big data and analysis, and writes case studies at Big Data Farm. Liu has been a panellist and guest speaker for the UC Berkeley Data Analytics Bootcamp. She is also a presenter at IBM conferences.
SendaGopalakrishnan – A Senior Staff Architect at Tesla, SendaGopalakrishnanis an expert in data architecture and analytics product development. Before Tesla, she worked with GE Healthcare as a Senior Data Analytics Architect. Sendahas also worked with MobiTV and Qualcomm in her early career.
1960 Computerised database starts being used
1970 Relational Database Management System (RDBMS) gains popularity
1980 SQL becomes the standard and most commonly used query language
1990 Client-server database systems start getting used for accessing computer systems with legacy data/ The demand for internet database connectors (eg. Front Page, Active Server Pages, Java Servlets, Oracle Developer 2000, etc.) rises
2000 Microsoft, IBM, and Oracle become the three leading database companies in the western world