- Duplicate, missing, inconsistent or badly formatted values are getting in the way of analysis.
- A raw export needs to be reshaped or derived into an analysis-ready structure.
- Compatible files or exports need to be mapped and consolidated into one coherent dataset.
- A coherent dataset needs to be explored and visualized to understand its characteristics, patterns and notable observations before deeper analysis.
Data Services
Data Cleaning & Exploration
Clean, prepare, consolidate or explore business data so it is more reliable, understandable and useful for analysis and decision-making.
THE QUESTION THIS SERVICE HELPS ANSWERCan this data be cleaned, structured, explored and made useful?
WHEN THIS SERVICE IS USEFUL
Turn messy or unfamiliar business data into a more reliable and understandable analytical source.
Cleaning, preparation, consolidation and exploration solve different parts of the same data problem. The selected option determines whether the work focuses on quality, structure, combining compatible sources, or understanding a coherent dataset through exploratory analysis, visualization and summarization.
- Which data-quality problems materially affect the intended analysis?
- How should fields, dates, categories and identifiers be standardized?
- Can directly related sources be joined without creating duplicate or misleading records?
- What distributions, patterns, relationships or unusual observations are visible in the data?
- What limitations remain after the data has been processed or explored?
Data Services
Data Cleaning
Clean and standardize a coherent dataset.
$199 USD- Identify and address relevant duplicates, missing values, inconsistent formats and obvious data-quality issues
- Standardize fields needed for the stated use
- Validate the cleaned output and document material changes
You receive: Cleaned dataset · Cleaning and data-quality summary
Data Services
Data Preparation
Restructure data for defined analytical or reporting purpose.
$249 USD- Review the raw structure against the stated analytical purpose
- Reshape, derive or standardize fields reasonably required for that purpose
- Validate the analysis-ready structure and document preparation decisions
You receive: Analysis-ready dataset · Preparation and field-structure notes
Data Services
Data Consolidation
Combine compatible sources into structured dataset.
$299 USD- Map directly related sources and joining fields
- Combine compatible records into one structured analytical dataset
- Check joins, duplicates, row counts or totals where applicable and document source relationships
You receive: Consolidated dataset · Source-mapping and consistency notes
Data Services
Data Exploration
Explore a coherent dataset to understand its structure, distributions, patterns, relationships and notable observations through exploratory analysis and visualization.
$299 USD- Profile the dataset and examine relevant variables, distributions and data characteristics
- Explore relevant patterns, relationships, group differences, unusual values and potential anomalies
- Create appropriate exploratory visualizations to make material patterns and observations easier to understand
- Summarize the main exploratory findings, data limitations and areas that may warrant further analysis
You receive: Exploratory data analysis · Relevant exploratory visualizations · Summary of key findings and data limitations
STANDARD SCOPE
What the fixed price covers
- Respective service corresponds to a data set or a set of related data sets
- Normal inspection, validation and documentation required to complete that selected option
- Exploratory checks required to support data-processing work, or exploratory analysis and visualization when Data Exploration is the selected option
- Delivery of the agreed dataset or exploratory output plus relevant notes, findings and limitations
OUTSIDE STANDARD SCOPE
What should I do?
- Let's make a custom project
- Explain to us what you need and our analyst will support you in finding a solution
- You can also request for an online consultative meeting to discuss your project.
CUSTOM PROJECT
Need something different?
Use another standard service for the follow-on analytical work. Contact Averidi before ordering when what you need is beyond the scope of this service.
Discuss your project ↗WHAT YOU'LL RECEIVE
Deliverables
- Data prepared according to the agreed data operation.
- Relevant data-quality, preparation or exploratory notes
- Summary of material changes, findings and limitations where applicable
WHO IT'S FOR
Suitable for
- Businesses with messy, inconsistent or unfamiliar data
- Teams preparing data for analysis or reporting
- Businesses that need compatible sources brought into one usable structure
- Businesses that need to understand a dataset's characteristics and notable patterns before deeper analysis
WHAT WE NEED
Inputs
- CSV, Excel or similar tabular business data
- Context or data definitions where available
- The intended analytical or reporting use where relevant
HOW THE ANALYTICAL WORK IS APPROACHED
A method shaped around demystifying the data.
Messy or unfamiliar data can block useful analysis. Choose the option that matches the data need: clean a coherent dataset, prepare it for a defined analytical purpose, consolidate compatible sources, or explore the data to understand its characteristics and notable patterns.
01Work from intended use
Cleaning, preparation and exploration decisions are tied to how the dataset will be understood, analyzed or reported so changes and exploratory analysis remain connected to the purpose of the data.
02Explore systematically
When Data Exploration is selected, examine relevant variables, distributions, relationships and unusual observations, using appropriate visualizations to make material patterns easier to understand.
03Preserve traceability
Material transformations, assumptions, source relationships and exploratory findings are documented so the delivered output can be understood.
04Validate and summarize
Key fields, joins, row counts, totals or analytical observations are checked where applicable, and material findings and limitations are summarized without presenting exploratory patterns as proven causes.
WORK INCLUDED WHERE RELEVANT TO THE AGREED SCOPE
- Review the supplied data against the selected option and intended use
- Resolve relevant missing, duplicate, inconsistent or structural issues where required by the selected option
- Examine relevant distributions, patterns, relationships and unusual observations where exploration is selected
- Use appropriate visualizations to support exploratory understanding where relevant
- Validate the resulting data or analytical observations as applicable
- Document material findings, changes, assumptions and remaining limitations
HOW THE PROJECT MOVES
Review before commencement.
Ordering does not silently move straight into analysis. Averidi reviews the project first and keeps the confirmed timeline visible in the workspace.
01Order
Place the order and provide the project details.
02Data & payment
Add available data and complete any required one-time payment.
03Project review
We review the scope, information and available data.
04Clarify if needed
If something is unclear, we contact you before work begins.
05Commence
You receive a commencement notification and confirmed deadline.
06Analyze & deliver
We complete the work, quality checks and agreed deliverable.
CAPABILITIES
What can sit inside this service.
The work is focused on finding the right solution for the customer. Our analyst takes a deeper look at the data to identify what useful information can be obtained from it and advise the customer on the best way forward.
01Data cleaning✓
02Data preparation✓
03Data consolidation✓
04Data exploration✓
05Data visualization✓
06Summarization✓
07Data-quality validation✓
SERVICE FAQ
Questions to settle before ordering.
Which option should I choose: cleaning, preparation, consolidation or exploration?+
Choose Data Cleaning for quality and consistency issues, Data Preparation when one dataset must be restructured for a defined analytical use, Data Consolidation when compatible related sources need to become one structured dataset, and Data Exploration when you need to understand a coherent dataset through exploratory analysis, visualization and a summary of key findings and limitations.
Does Data Exploration include business analysis?+
Data Exploration examines the supplied dataset to identify and communicate relevant characteristics, distributions, patterns, relationships and unusual observations. It includes exploratory visualizations and a findings summary, but a separate business-performance analysis, management report, dashboard, forecast or predictive model is outside the standard scope.
Can you combine data from multiple systems?+
Yes when the sources are directly related and can reasonably be mapped into one coherent analytical dataset. Ongoing integrations, pipelines or materially separate data domains require a different scope.
NEXT STEP
Start with Data Cleaning & Exploration.
Review the scope, or use the Service Finder if you are still deciding which service fits the project.