Data Engineering & Business Intelligence
Do you have a lot of unstructured data that could be used to benefit your business? Arcadia can help you capitalise on the power of data analytics and reach your strategic goals with data engineering and business intelligence services.
Data engineering is the science of collecting, storing, processing and visualizing data, as well as the provision of various means of sharing this data with others.
Business intelligence (BI) is a set of technologies, applications and practices that transform data into meaningful information that helps organisations make data-driven decisions.
What We Do
Analyse data and looking for insights
To apply data analytics to business processes, companies must first develop a strategy and a plan. This can be a tedious task, particularly when the data are often scattered and unformatted. Getting help to develop the strategy and identify the business benefits is a critical first step.
Create centralised data warehouse for analytics
Businesses generate a large amount of data that is located in completely different IT systems. This makes it difficult to obtain and evaluate information. To solve this problem, we combine all data sources into a single repository.
Develop clear interactive reports
The quality of data analysis is highly dependent on the visual presentation of information. The better the data is prepared, the easier it is to draw the correct conclusion from it. To address this issue, we help clients create interactive online reports.
Any activity can be divided into multiple business tasks. To make effective management decisions, it is important to accurately understand the business problem and rely on fresh and verified data. To accomplish this, we automate data collection for analysis and provide quality control.
Explain complex things in simple terms
The knowledge gained during analysis can only be useful if it is 100% understandable to business users. We know how to find the right words to explain complex technical phenomena as simply and succinctly as possible.
Data Engineering Work Process
Collect data from different software systems, sensors, instrumentation, logs and user‑generated content.
Move & Store
Configure data flows, pipelines and ETL process and setup storage of structured (databases) and unstructured data (documents, images and video files).
Clean data, detect anomalies and unify data coming from different sources.
Make data available for analysis with different tools, including Power BI, Tableau, Spotfire and Qlik.
Technologies Our Data Engineers Use
Big Data Tools
Featured Case Studies