Business Intelligence & Analytics Software
Business Intelligence Developers cover a varied range of roles and responsibilities such as capturing user requirements, generating visualisation design, unifying data sources, developing performance management dashboards and supporting existing applications. What BI tools you need depends on how your data is currently managed and how you would like to analyze it. For example, if it is currently scattered across disparate transactional databases, you might need to build a data warehouse to centralize it and invest in data management tools that offer Extract, Transform and Load (ETL) functionality to move and re-structure it.
Graduates will gain a set of marketable skills ranging from basic learning of SQL (Structured Query Language) programming and other business intelligence specific software knowledge, to more managerial abilities such as the capacity to improve operational efficiency, increase financial performance and communicate strategic solutions.
BI programs can also incorporate forms of advanced analytics , such as data mining , predictive analytics , text mining , statistical analysis and big data analytics In many cases though, advanced analytics projects are conducted and managed by separate teams of data scientists , statisticians, predictive modelers and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.
For example, it is unlikely that an API developer is going to want data consumers running queries that take any longer than a few seconds, consequently, I experienced numerous timeout issues and had to break the ETL load down into ‘micro’ batches with the ability to retry the query X times.
In addition, Hadoop systems are increasingly being used within BI architectures as repositories or landing pads for BI and analytics data, especially for unstructured data , log files, sensor data and other types of big data Before it’s used in BI applications, raw data from different source systems must be integrated, consolidated and cleansed using data integration and data quality tools to ensure that users are analyzing accurate and consistent information.