Who are the data professionals and do we need them?

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Photo by Ali Hajian on Unsplash

Essential data science skills include:

Data Collection and Preparation

To work with data, we need data. The data collection process includes all processes and methods through which data is collected for analysis. While there are free datasets available in sites such as Kaggle or Google datasets.

Data visualization

Data visualization is an important aspect when working with data. From exploring data to discover trends and patterns to carrying out some basic statistics on the data and even reporting the findings from the data, Data visualization plays a key role in the data science process.

Programming

Some level of programming is also required depending on your job role. It can be an added competitive advantage that sets you apart from other candidates.

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Your Data Science Team

Data Analyst

Data Analysts perform a number of tasks including collecting data, carrying out statistical analysis, building data models and reporting. It is the data analysts job to turn data into useful insight for the company.

  • R
  • Python
  • JavaScript
  • HTML
  • C/C++
  • Database systems
  • Data visualization
  • Mathematics and statistics
  • Spreadsheet tools
  • Presentation skills
  • Communication tools
  • Machine Learning
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Data Scientist

Probably the most common job role in data science (and broadest), the Data Scientist is one skilled in computer, statistics, analysis and mathematics.

  • Python
  • R
  • MATLAB
  • SAS
  • Predictive modelling
  • Mathematics
  • Statistics
  • Machine learning
  • Data wrangling
  • Exploratory Data Analysis
  • Ability to use Big Data tools
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Database Administrator

The database administrator is responsible for the management of a companies database. The database administrator plays a key role in the selection of software and hardware components of a database. The also ensure the integrity of the data and ensure the database security. The database administrator essentially acts as the Protector of the data.

  • XML
  • Python
  • C#
  • Ruby
  • Database queries
  • Database design
  • Knowledge of Relational Database Management Systems
  • Data security
  • Data modeling
  • Data backup and recovery
  • Storage technologies
  • Operating systems
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Data Engineer

The insights you draw from data, can only be as good as the data available. The data engineer creates a pipeline or data feed that automates the data collection process to on-site or cloud storage systems. The data engineer makes data easily accessible to end users (such as the data scientists, data analysts), the data engineer is a team player, working hand-in-hand with data scientists and analysts to ensure that the required data is available in the right format for easy analysis.

  • transforming the data
  • Loading data into destination(database, data warehouse)
  • Data synchronization
  • Programming (Python, C++, Java)
  • SQL
  • Database Systems
  • Data warehousing solutions
  • Machine Learning
  • Data modeling
  • Big Data tools — Hadoop
  • Data Visualization skills
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CONCLUSION

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Data Science Nigeria PH community. Data Science and Artificial Intelligence

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