Data Modelling, Data Warehousing & Big Data

It helps to improve query usage performance, increase user efficiency and improve user experience. It also improves the data quality through model development (i.e. data redundancy)

Big data is using all data for analysis and processing without shortcuts such as random analysis (sampling survey). The four characteristics of big data are Volume, Velocity, Variety, and Value (aka 4V). Big data is a massive, high-growth and diverse information asset that requires new processing models to have stronger decision-making power, insight discovery and process optimisation capabilities.

The main reason is because of the increase in volume of data as well as the speed it’s transmitted. In addition, Big Data also reflects an increase in the complexity of the types of data collected, such as images, videos, sounds and unstructured text, that render traditional data processing techniques slow or even unusable.

Data Warehousing is the process used to collect and manage data from different sources to provide meaningful business insights. Data warehouses are often used to connect and analyse business data from various systems. The Data Warehouse is the core of the Business Intelligence system and is built for data analysis and reporting.

Data Warehousing on-premises means that the organisation has total responsibility for the software and hardware used, as well as having to constantly update both. The processing and storing capabilities are fixed, unless a large project is undertaken to update systems. Data Warehousing in the cloud means that the update of hardware and software is undertaken by the provider and requirements for processing and storing can be scaled in line with the changing needs of the organisation.

At Talan, we play a pivotal role in supporting data modelling, data warehousing, and big data with our clients. In the realm of data modelling, we collaborate closely with clients to understand business requirements, ensuring that conceptual and logical data models accurately represent the underlying business processes.  Our specialists in database technologies transform the data models into efficient and effective data warehouses. In the context of data warehousing, we contribute by designing, implementing, and maintaining the architecture that supports the storage and retrieval of structured data.  Additionally, in the era of big data, we leverage our knowledge to handle vast and diverse datasets, employing technologies like Hadoop, Spark and those offered by major Cloud providers. We are instrumental in implementing scalable and robust solutions that enable the business to gain valuable insights from large volumes of data, which in turn fosters informed decision-making.