Data Warehousing

Solid data science foundations

The Problem

You can't do data science without data. Traditional data warehouses are not designed with data science in mind.

How can you build your data infrastructure so that you don't spend a disproportionate amount of time transforming and cleansing data for each project?

The Solution

Our expertise in data warehousing, from traditional SQL systems, NoSQL / hybrid systems such as BigQuery and graph databases such as Neo4j leaves us ideally positioned to help you design and build your data warehousing for data science.

We can help you to remove the bottlenecks caused by inadequate data architecture from your data science workflow, allowing you to spend more time on analysis and improving models.

We also deliver a full optimisation of your SQL scripts and ETL processes and provide training sessions on data warehousing best practice.

Inputs

Your operational or reporting data

Time with key internal stakeholders including marketing, product and dev ops

Deliverables

1. A full evaluation of your current data warehousing set-up, including your ETL and scripted data pipelines.

2. A proposal on the best technologies for your use case, including data visualisation and third party tools for A/B testing, CRM and Voice of the Customer surveys.

3. A detailed plan on how to move from where you are, to where you need to be and optionally, a full implementation of the plan by our data specialists

Outcome

You'll come out with a robust, reusable source of accurate data that can be easily consumed for data science and other analytics needs.

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