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Data and Analytics

Extracting insights, analysing, collecting, organising and storing of data.

Data analytics is focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organisation and storage of data.

Statistical analysis and technologies can be applied to the data to find trends and solve problems. Data analytics has become increasingly important as a means for analyzing and shaping business processes and improving decision-making and business results.

Data analytics is used to perform analysis on data in an effort to describe, predict, and improve performance. To ensure robust analysis, Connaught use a range of data management techniques, including data mining, data cleansing, data transformation, data modeling.

Many companies are collecting a lot of data but in its raw form the data is not really helpful. Data analytics is the process of analysing data in order to draw out meaningful, actionable insights. These insights can then be used to improve business decisions.

Data Analysis is the process of extracting raw data, organising, analysing and often presenting it in a coherent, intelligible way.

Data analytics is a form of business intelligence, used to solve specific problems and challenges. It’s about finding patterns in datas which can tell you something meaningful, useful and relevant e.g. how customer groups behave.

Data analytics helps you to make sense of the past and to predict future trends. It enable you to make informed choices based on the data. Data insights enable you to develop a deeper understanding of your audience, your business sector and your company.

What can data analytics used for?

Examples of data analytics inlude:

  • To predict future sales and purchasing behaviours
  • For security purposes e.g. detect, predict and prevent fraud within the finance, insurance and banking industries
  • To evaluate and optimise the effectiveness of marketing and advertising campaigns
  • To identify and eliminate bottlenecks and weaknesses
  • To boost customer engagement, acquisition and retention
  • To develop risk management solutions
  • To identify opportunities for innovation, increase efficienies and create new revenue streams