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AB Microfinance Bank Nigeria is a foreign-owned financial institution, based in Lagos state, which offers a broad range of financial services to micro, small ...
Ascentech Services Ltd acts as a gateway to provide a wide range of recruitment and selection services to companies. We are a dedicated team of professional ...
NewGlobe supports visionary governments to transform public education systems, the cornerstone of a prosperous, equitable, and peaceful society. With a ...
Betensured provides football betting predictions, detailed analysis, betting tips, football form and statistics, the latest results and so much more! ...
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Project Growth champions remote flexibility, prioritizes employee well-being, fosters inclusivity, and cultivates a culture of continuous learning and ...
The West African Centre for Public Health and Development (WACPHD) is a non-governmental organization working on Improving health equity through sustained ...
Noemdek's advisory practice was established to support international strategic advisory firms with relevant local expertise. We are able to deliver on our ...
Vennote Technologies Limited is a well-established ICT company with experience spanning over two decades in enterprise solutions using best of breed products ...
Davidorlah Farms is a pineapple farm estate developer and management service company that specialises in pineapple farming and distribution of all kinds of ...
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Mshel Homes Limited is an independent Real Estate Company located in Abuja, Nigeria. Simply put; we partner with You to get your dream home. Make all the right ...
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.
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.
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
Google Sheets
SQL
Microsoft Excel
SAS
Tableau
R or Python
Jupyter Notebooks
Microsoft Power BI