Today, such concepts as “big data” and “real-time” analytics are strongly entering the enterprise world. Data-driven decision-making has proven to outperform intuition and questionable judgement. How can companies tackle advanced data technologies to achieve their goals? Which issues can they face? Here are several things to avoid on their data science path.
1. The absence of defined metrics.
Data collection is only the first step towards a data-driven organization. Interpreting results and making corresponding actions is what determines the efficiency of your undertakings. Defined metrics enable you to contextualize the data in a proper way.
