Data

Data organized around the way your business works.

Organize, standardize and validate information so scattered files and sources become a more usable dataset.

The starting point

The information exists. Making it usable takes work.

Different field names, incompatible formats and rules only one person knows can make data difficult to use. The first step is to understand where those differences come from and what needs to be consistent.

Dates, values and identifiers in different formats.
Duplicate, incomplete or conflicting records.
Information spread across files and systems.
Data entry and validation rules that are not documented.

How we can help

Give data a structure and a clear set of rules.

Data processing follows the agreed purpose and rules. An apparent difference is not always an error, so cleaning and consolidation decisions need to account for the context.

Gather and structure

Obtain information from authorized sources and organize it into a structure suited to its intended use.

Standardize and check

Apply rules for format, consistency and duplicates, recording cases that need a decision or review.

Prepare the output

Organize the data and validation records in the format defined for the next step in the process.

Before we begin

Data quality needs a shared definition.

The assessment considers the purpose, data sources and access permissions. Volume, update frequency and quality criteria help establish what can be delivered and which limitations need to be made clear.

What will the data be used for?
Which sources and fields are needed?
What makes a record valid or a duplicate?
Who decides how to handle issues that cannot be resolved automatically?

Possible deliverables

Organized data, with the rules behind it.

The proposal defines the deliverables relevant to your needs. Depending on the scope, they may include:

A structured dataset in the agreed format.
A data dictionary and field requirements.
Validation rules and a report of inconsistencies.
A reproducible workflow, with instructions and known limitations.

Data and automation

Organized information can support the next workflow.

When updates are recurring, processing rules can become part of an integration. Feasibility depends on the systems, permissions and operating environment; responsibility for operation and maintenance needs to be agreed.

Explore integration and automation

Working with data

From the source file to its intended use.

Can you work with existing spreadsheets and files?

Yes, this can be part of the scope. The formats, volume, structure and usage permissions are assessed first, along with the result you need.

What happens when the data is incomplete?

Rules can identify and flag these cases for review. How they are handled depends on the purpose and available sources; missing information is not invented to fill the gaps.

Does the delivery include a dashboard?

Only when it is included in the proposal. Organizing and validating data can be a standalone project or preparation for a later analysis and visualization stage.

Do I need to send the full dataset when I first get in touch?

No. Start by describing the sources, formats and difficulty you are facing. If a sample is needed, we will agree on a suitable way to share it. Do not include confidential data in your initial message.

Let's understand your sources

What is preventing your business from using its data better?

Describe where the information comes from, how it is used today and the problem you want to solve.

Discuss a project