Too often, it produces work which looks and feels technical to business people who therefore struggle to meaningfully link it to the challenges they face in the real world. Instead, analytics requires continual input and validation from those who asked for the work to be done in the first place.ДЄnalytics is a means to an end and not an end in itself. Like the best system development projects, good analytics does not focus on documenting business requirements only to submerge them in an opaque process. Alignment also requires an analytics process, which enables close and continuous contact to be maintained with business sponsors so that course corrections can be made and new information assimilated throughout. This starts with the need to fully understand the business issue or opportunity at hand and then selecting the data and techniques most appropriate to ensure a continuous focus on producing what your stakeholders need to make real-world business decisions.

What are the best practices? In my opinion there are three key conditions that have to be satisfied in order to consistently performing at a high level: Strategic data analysis: Monitoring and analysis of trends observed in data to produce conclusions with significant business meaning and strategic impact.

Predictive modeling: The application of statistical modeling techniques to predict prospect or customer behavior.Дata-driven segmentation: The use of clustering or other techniques to organize prospects or customers into meaningful groupings for business management. The answer is to follow best practices-in people and processes.ДЇirst, letвЂ™s define вЂњanalytics,вЂќ a term with a variety of different interpretations. What does it take to produce great analytics? Some would say itвЂ™s all about the right data, tools and techniques.

Data analysis best practices