CDA program CDA Certification Standards Why CDA Program? How to be a CDA? About Exam

Introduction of Certified Data Analyst

CDA (Certified Data Analyst) aims at not only being specializes in data acquiring, cleaning, processing, analyzing, but also producing business reports and providing decision-making data analysis talent in the industries such as, Internet, retail, financial, telecommunications, medical, and tourism, etc.By adhering to the summary and concise of the most advanced business data analysis practice as its mission, and analyzing knowledge systems of various practitioners in data analysis as its duty,

CDA aims at promoting global data analysis talents be more standard, scientific, and professional. In the meantime, improving data analysts’ professional quality and ability, thus promoting the high quality and sustainable development of data analysis industry.

"CDA Certification" is a series of professional, scientific, international and systematic talent evaluation standards. Divided into CDA LEVEL Ⅰ, LEVEL Ⅱ, LEVEL Ⅲ,

CDA involves essential skills for big data and data analysis practitioners in finance, electricity, medical, Internet, telecommunications and other industries. It meets the global big data and data analysis technology trends, and provides data analysis reference standard for companies and organizations. Home of Economy and Management is the only organizer of CDA Certification Exam in China.By attending offline exams hold in the end of December every year, one who passes the exam will obtain CDA Certification.

CDA LevelⅠ：Business Data Analyst.

Specifically, government,finance, telecommunications, retail and other industries front-end business personnel; Engaged in marketing, management, finance, supply, consulting and other positions; Non computer professional personnel statistics, background and career employment entry zero basis.Business data analysts need to master the basic theory of probability and statistics.Able to skillfully use Excel, R, SPSS, SAS and other professional analysis software.Good business understanding.According to the business problem index,use common Data analysis methods to data processing and analysis,And draw a clear logic business report

CDA Level Ⅱ: Modeling Analyst.

More than one year working experience in data extracting Or passed through the CDA Level Ⅰ certification. Specializes in data analysis and data mining personnel of government, finance, telecommunications, retail, Internet, electricity, medicine and other industries.Requires knowledge of multivariate statistics, time series, data mining theory based on Level 1. Master advanced data analysis methods and data mining algorithms.Able to skillfully use SPSS Modeler, SAS, PYTHON, R and at least one professional analysis software. Familiar with the application of SQL access enterprise database, combined with business, can extract relevant information from massive data.modeling and analysis From the different dimensions, Form logical and rigorous data analysis report which can reflect the overall data mining process.

CDA Level Ⅱ: Big Data Analyst.

Data analysis position working experience more than one year, or passedCDA Level Ⅰ certification. Points to the government, finance, telecommunications, retail, Internet, electricity, medicine and other industries specializes in data analysis and the cloud of big data. In Level Ⅰ requirements on the basis of the knowledge of the JAVA language and Linux operating system, to grasp the use of Hadoop, Spark, Storm and other professional large data architecture and analysis software, to extract information from huge amounts of data, and to combine the R, python, such as software, form a rigorous data analysis report.

CDA Level Ⅲ: Data Scientist.

More than 3 years working experience in data extracting Or passed through one of CDA Level Ⅰ certification. Specializes in Senior Data Analysis of government, finance, telecommunications, retail, Internet, electricity, medicine and other industries.Responsible for the development of enterprise data development strategy,Discover enterprise data value.Improve enterprise operation efficiency, increase enterprise value.Able to lead the team to effectively integrate and manage the data assets.Establish internal and external data connections; data planning capability