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Data Analyst Jobs in Ondo, Nigeria

View Data Analyst jobs on TechTalentZone
  • eHealth4everyone logo

    Data Analyst – Post Abortion Care (PAC) Project

    eHealth4everyoneEnugu, Akwa Ibom, Benue, Ekiti, Kebbi, Ondo, Taraba, Zamfara, Nigeria21 October

    eHealth4everyone is a leading digital health social enterprise dedicated to making the world healthier. We are a new kind of mission-driven organization with ...

    Onsite
  • Golden Oil Industries Limited logo

    Data Analyst

    Golden Oil Industries..Ondo, Nigeria11 September

    Golden Oil Industries Limited was incorporated in Nigeria on 8th September 1988. Golden Oil Industries Limited has grown into a household name in Nigeria's ...

    Onsite
  • Medecins Sans Frontieres logo

    Data Analyst Activity Manager

    Medecins Sans Frontie..Ebonyi, Abuja, Edo, Ondo, Nigeria08 May, 2024

    Médecins Sans Frontières (MSF) is an international, independent, medical humanitarian organisation that delivers emergency aid to ...

    Onsite
  • Jhpiego - John Hopkins University logo

    Data Analyst

    Jhpiego - John Hopkin..Ondo, Sokoto, Nigeria29 February, 2024

    "What are we aiming at?” That’s the question our first president, Daniel Coit Gilman, asked at his inauguration in 1876. What is this place all ...

    Onsite

Who is a data analyst?

A data analyst is a professional who retrieves, organizes and analyzes information from various sources to help an organization achieve business goals. Data analysts use logic, statistical techniques and computer programming to turn numbers into information that an organization can use to improve workflow and business processes. 

An important goal of the analysis is to distinguish between what data is important and what data should be given less weight. In many organizations, data analysts are also responsible for data quality and preparing reports for internal and external stakeholders.

What is the role of a data analyst?

  • Developing and implementing databases and data collection systems: Data analysts create and manage databases and data collection systems that efficiently gather relevant information.

  • Identifying critical KPIs and setting priorities: Collaborating with management, data analysts help determine the most crucial Key Performance Indicators (KPIs) and establish priorities for the company.

  • Gathering information from original and secondary sources: Data analysts acquire comprehensive information for analysis by gathering data from various sources, including primary and secondary sources.

  • Sorting and sanitizing data: Prior to analysis, data needs to be organized and cleansed to ensure accuracy and quality.

  • Identifying trends and patterns in large datasets: Data analysts utilize advanced analytical techniques to uncover meaningful trends and patterns hidden within extensive datasets.

  • Creating visual representations of data: Data analysts employ data visualization tools to present insights in a visually appealing and understandable format, enabling stakeholders to easily comprehend complex information.

  • Generating and modifying reports: Data analysts develop reports that summarize their findings, providing actionable insights and recommendations for decision-making purposes. These reports are continually refined and adjusted based on evolving data analysis requirements.

  • Building and maintaining dashboards: Data analysts design and maintain interactive dashboards that offer real-time visualizations of key metrics, allowing stakeholders to monitor performance and make informed decisions.

  • Documenting data models, metrics, and infrastructure: Data analysts document the data models, metrics, and supporting infrastructure they create and maintain to ensure data integrity and facilitate collaboration.

What skills do you need to be a data analyst?

  • Scripting: SQL, Python, and R

  • Data blending: Informatica, Alteryx, and SAS

  • Data visualization: Excel, Tableau, Power BI, D3.js, and ElasticSearch

  • Machine Learning: TensorFlow, Keras, PyTorch, and Pandas

  • Practical database querying

  • Data management

  • Data cleaning

Data analyst tools

  • Google Sheets

  • SQL

  • Microsoft Excel

  • SAS

  • Tableau

  • R or Python

  • Jupyter Notebooks

  • Microsoft Power BI