Driven by the Consolidata Data Platform...
The choice of applications that make up Consolidata's technology stack are not just a list of cool data tech – they are the fundamental building blocks of the Consolidata Data Platform – and the list is continually growing as we expand the Platform. Below we discuss our main technologies and why we use them.
Consolidata embraces cloud technologies. The Consolidata Data Platform is delivered through our secure infrastructure on Microsoft Azure and Rackspace Cloud.
Microsoft SQL Server 2016
The Microsoft stack has long been trusted by businesses large and small. Consolidata adopted Microsoft SQL Server in its infancy (SQL Server 7), and have expert knowledge of implementation best-practice and performance capabilities of Microsoft's Business Intelligence stack. Ideal for handling transactional and relational data, Microsoft SQL Server 2016 ensures the secure storage, quick processing and rapid retrieval required in a robust business intelligence environment.
If you're wondering whether SQL Server isn't up to the job, try this. For one of our current clients, we are running monte carlo simulations on a dataset of 8 billion rows at a rate of 1.5 billion records an hour.
Relational isn't everything. Unstructured data tools can provide advantages over relational databases in specific data applications. This might be desirable for a big data application, a distributed compute platform, or if you want to build powerful predictive models and examine relationships in large data sets. Consolidata are experts in Hadoop, Hive, Sqoop, Spark and Pig as well as Neo4j graph database and MongoDB.
On Azure, we take advantage of Microsoft's Data Lake service to manage IoT device and event stream data.
Analytics and Advanced Analytics
'Data is worthless if it cannot be analysed' - Oliver Frost
SQL Server Analysis Services
SSAS supplies high-performance analytics for the decision makers in the business. By drilling down into your data inside a tabular model or multidimensional cube, our clients can intuitively explore new patterns and trends in their data.
R, R Server and Python
We use open-source statistical tools like R and Python. These are our weapons of choice for delivering:
- quick and effective data cleaning
- data wrangling
- large-scale data aggregation
- data enrichment
- opportunities for machine learning and training data
In 2016, we adopted Microsoft R Server, which provides a performance benefit where open-source R lacks. We use MRS to build powerful predictive models over very large datasets, and SQL Server 2016 harnesses the power of R over relational databases.
We use Azure ML to build predictive and prescriptive analytics models for our clients.
Reporting, Dashboards and Visualisation
Data-driven and algorithm-driven business comes into its own when the insights gained are channelled back into the business and used to change the existing business processes for the better. The key to developing a narrative around your insights is to use a solid visualisation or reporting solution.
Power BI can be used to build dashboards that combine insights from multiple locations, into a single, combined view. Engage with interactive, self-service reports and visualisations, drill down into data and paint a picture with your results.
Reporting Services and XLCubed
SQL Server Reporting Services and XLCubed provide scalable reporting options.
Discover more about these technologies and how we use them on the Consolidata Data Platform. Engage Consolidata