In this data analytics course you learn to turn a business question into a sound analysis and to communicate the results clearly. It is aimed at professionals in finance, marketing, sales and operations who analyse data regularly or are moving into that role. You frame questions, clean datasets, check data quality, analyse with Python and pandas and prepare charts for decision makers. The focus is on a traceable method rather than on individual tools.
What you’ll take away.
- Derive a measurable analytical question with suitable metrics from a business question
- Check datasets for missing values, duplicates, outliers and type errors and clean them
- Filter, group, merge and condense data into metrics with pandas
- Read descriptive statistics, distributions and simple correlations correctly and distinguish them from causation
- Prepare results as a chart and a short recommendation for a business audience
Your training in detail
- Who is it for?
- Professionals from finance, marketing, sales, production and administration, as well as career changers moving into data analysis.
- Prerequisites
- Confident use of Excel or spreadsheets. Basic SQL or Python helps but is not required.
- Format & planning
- Suggested format: 3 days live online or on site. Scope depends on prior knowledge.
Agenda: from understanding to application
Our independently developed agenda proposal. Focus areas, lab environment and scope are agreed before booking.
Framing the question: target variables, metrics, hypotheses and distinguishing analysis from routine reporting.
Getting data: reading CSV, Excel and SQL queries, documenting data sources and respecting data protection limits for personal data.
Data quality: missing values, duplicates, date and text formats, outliers and when cleaning distorts the finding.
Analysis with pandas: DataFrames, groupby, merge, pivot_table and time series compared by month and quarter in a Jupyter notebook.
Everyday statistics: mean and median, spread, correlation, sample size and typical fallacies such as spurious correlation.
Communicating results: choosing charts with matplotlib, labelling, a one-sentence takeaway and a recommendation with assumptions and limits.
Suggested exercise: You analyse a sample sales dataset, find the cause of a revenue decline and summarise your recommendation on one page.
Exams, licences & credentials
The course is vendor-neutral. If you use Power BI, the Microsoft exam PL-300 is a possible next step, although this course does not specifically prepare for it. Fees are only included if confirmed in the offer. Attending alone does not award a vendor certification.
Vendor references & review date
Sources checked on 2026-11-03. These sources describe the technology or external exam requirements. They do not imply a partnership with NextNowa.
Your learning content
These objectives describe the training topic. The specific syllabus, duration, dates, trainer and price are agreed before booking.
Frequently asked questions
Do I need Python for data analytics?
Not necessarily. Many analyses work well in Excel or SQL. Python with pandas pays off when data volumes grow, steps need to be repeatable or several sources are combined. In the course you learn the approach independently of the tool and see when moving to code is worthwhile.
What is the difference between data analytics and data science?
Data analytics answers concrete business questions with existing data, usually descriptive and diagnostic. Data science often goes further and builds predictive models with machine learning. Analysis is the foundation, so this course is a sensible starting point before you specialise in models.
How do I know whether my data is good enough for an analysis?
Check completeness, uniqueness, timeliness and plausibility: are values missing, are there duplicates, do time periods and units match, can outliers be explained? You should also ask whether the data actually reflects the business question. In the course you practise this check with a fixed checklist.
Does Data analytics include a certificate?
The course is vendor-neutral. If you use Power BI, the Microsoft exam PL-300 is a possible next step, although this course does not specifically prepare for it. Fees are only included if confirmed in the offer. Attending alone does not award a vendor certification.