Delta Science  Get in touch

Getting Data Right

Generating insights involves managing both,
the data pipeline and the process of insight generation 

Drowning in data, but lacking actionable insights to enable vital business decisions? Having no systematic plan how to gather the empirical information actually needed? Needing support in your data engineering team to do the heavy lifting? 

We can help you in your data challenges in the following areas :

  • Data Engineering

  • Data Science

  • Digital Research
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Digital Research, Data Science & Data Engineering

Scope Of Expertise

Digital businesses and project teams might face diverse challenges in terms of data availability, access and/or data usage. We can help you orchestrating, integrating and even fixing crucial elements of your data process such as...

ELT/ETL Data Pipelines

Moving and enriching data to serve the whole spectrum of  business use cases is pivotal for the success of every data-driven organisation

Dimensional Data Modelling

Storing & accessing data effectively entails organising them into facts and dimensions, ultimately creating a relational model 

Cloud Computing / Storage

Building high-performance data pipelines using leading cloud platforms like Snowflake, Databricks or Confluent and transformation tools such as dbt

Ideation / Exploration

Finding the right business area to drill & selecting the right experimental approach that matches your core question

Experiment Design / Setup

Defining, implementing & monitoring all experimental and technical details to collect unbiased high-quality data

Lean Analytics / Tracking

Measuring only what you really need to get the answer that matters most for your current business providing a solid base for iteration

Data Science / Analysis

Based on a coherent data analysis strategy implementation of all entailed coding steps: data processing in Python, R, SQL or Matlab

Validation / Quantification

Quantifying the explanatory power of the collected data in reference to the core assumption: incl. statistical analysis & data visualisation

Evaluating Digital Devices

Do users or patients really profit from the digital device as intended? Developing & following a systematic evaluation concept (e.g. clinical trial) will provide critical data

Data Science, Data Engineering & Digital Research
Moving Forward

Data Engineering & Data Science

Making data available and providing them in a consumable way is essential for downstream analysis.

Data availability and accessibility are necessary for generating insights.  Insight generation is a modular and iterative process starting with a clear-cut question (hypothesis), extending to experimental design and setup, implementing data collection/selection and control, defining a systematic analytics strategy and building a clean data analysis pipeline.

Following this process ensures that you get answers and remove uncertainty, while avoiding being stuck in data alone.
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Making It Happen: Step by Step

Pick The Level Of Support You Need

Our support is modular and adjustable making sure to leverage the resources of your project already in place, e.g. cloud infrastructure, data warehouses, analytical tools, reporting infrastructure, personal etc.
Data ScienceSolution Architecture: Live Data StreamingDigital ResearchDigital Research

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