Once the data is ready, there are various options which could be used for data analysis.
1. Charting Engines: These engines help in making sense of data by creating reports, dashboards, geographical dashboards, etc. There are free and open-source charting engines available in the market like D3, C3, Provtovis, etc. D3 is one of the most popular charting engines which is also developer-friendly and allows to custom-create new charts. There also exist paid charting engines like Fusion Charts, High Charts, etc.
2. BI Software: A mature BI software can provide sufficiently rich self-service interface allowing users to drag and drop to create reports and dashboards. BI software can also be categorized into open-source BI software (like Helical Insight, Japsersoft, Pentaho, etc.) and proprietary BI software (like Sisense, Tableau, Qlikview, etc). BI software can also be segmented as in-memory software or non in-memory software.
3. Analytics: Various analytical tools like R, Minitab, Python, etc., can be used to implement and derive trends from data. Based upon the use case, various kinds of algorithms or a combination can be used like linear regression, clustering, decision tree, conjoint analysis, etc.
Based on your requirement, budget, timeline and self-service capability requirement, we could help you in finding a data analysis tool that will be a perfect fit for your organization. We are also experienced with various kinds of data analytics algorithms and could build prediction models based on your use case.