BIG DATA Certification

Science Data and Big Data

Big Data is a term used to describe any set of data that is large or complex enough to make it difficult to deal with traditional techniques such as relational databases.

Data Science applied to Big Data includes activities that consist in identifying, collecting, structuring and analysing the masses of data generated today by the companies themselves (e-commerce servers, Industry 4).0, etc.), to improve existing processes, or to discover possible new applications from data sources. The “data” is nowadays considered as a strategy, just like energy in the past, we even speak of “data mining” to mean digging into a data mine.

Big Data solutions are often necessary when traditional technologies and know-how have reached their limits.

Big Data activities require specific skills, which are also included in the various third party activities carried out by companies. These have been the subject of extensive studies by OPIIEC and CIGREF in France.

Level 1 Certification: Big Data Foundation

The program is the result of the work carried out in 2016/2017 by specialists, which gave way to a “common core” BigData Foundation characterized by a “360°” vision with three main viewpoints on the fundamentals of Big Data:

  • Knowledge of definitions and terminology
  • Knowledge of Big Data activities
  • Knowledge of Big Data tools

Experts

  • 8 successive workshops brought together the project group which is made up of experts from two highly involved organisations:

THALES-Services offers its experience in the exploitation of Big Data  (data management/storage), Big Analytics (processing, enrichment and valorization of data) and Visual analytics (data exploitation and interactive visualization) for its aeronautical, space, land transport, security and defence markets.

ACTIVUS-Services, one of the best ESN of the Syntec classification for its work on the restitution of data collected through two main types of analysis: predictive in order to be able to anticipate interactions between objects, and aggregated in order to value and classify object behaviours on a community network.

The work done by the group of experts has also allowed us to define a Big Data certification scheme that positions 5 fields of work on 3 qualification levels:

  • In the Delivery sector, the architecture of technical solutions supporting Big Data on the one hand, and the Data Scientist and Data Analyst production business lines on the other hand.
  • In the Consulting and Assistance sector, the Data Engineer and Big Data Specialized Consultant businesses

Data Scientist Practitioner and Data Scientist Expert

The role of the Data Scientist is to explore, exploit, analyze and evaluate the richness of data in order to establish scenarios to understand and anticipate future fields or rational operations for the company; a statistician who analyzes the data to translate a Meteorological problem into a mathematical/statistical problem, and vice versa. Within this area of work, he/she compares and evaluates the different models or calculation methods and anticipates their advantages and disadvantages in a specific environment. Knowledge of relevant data repositories  enables him/her to make recommendations on data warehouses for consolidation, modification, repatriation, outsourcing and internalization.

The Data Scientist Practitioner certification (level 2 in the Big Data Certification Scheme) ensures that you have the skills to:

  • Apply techniques (statistics, text mining, behavioral, geo-localization,…) of information extraction and analysis obtained from data sources (Big Data)
  • Obtain appropriate data, find relevant data sources, make recommendations on the databases to consolidate, modify, repatriate, outsource, internalize, design datamarts, or even data warehouses.
  • Evaluate the quality and richness of the data, analyse it and report on the results to then integrate them into the target information system within the Business Line.
  • Analyze data to translate a field problem into mathematic/statistical problems, and then
  • Compare and evaluate different models or computational methods and anticipate the advantages and disadvantages in a specific environment.

The Data Scientist Expert certification (level 3 in the Big Data Certification Scheme) attests to the high level of technical competence in the field, as well as specific knowledge-based skills, which legitimates its holder to intervene at the organisation’s strategic level.

Data Analyst Practitioner

His/her role is to implement the IT tools, techniques and statistical methods that will allow the organization to synthesize and translate the company’s data. Positioned at the ISD where it provides analytical support for conducting exploration and complex data analysis, industrializing analysis processes and managing modeling and architecture operations of data repositories while ensuring consistency. As its title suggests, the Data Analyst Practitioner’s business is clearly focused on implementation-oriented work.

The Data Analyst Practitioner certification ensures that you have the optimum skills to:

  • Provide analytical support in the conduction of data exploration and complex analysis
  • Create data search algorithms to explore useful data
  • Industrialize the process for the most valuable data
  • Organize, synthesize and translate information to facilitate decision-making
  • Manage operations and administration, modeling and architecture of data repositories
  • Ensure that existing data organizations are functioning well and coherently
  • Assist the Data Scientist and the Data Architect in the implementation of predictive models and technical solutions.