This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the RadarUnderstand more
ProbarVale la pena intentarlo. Es importante entender cómo construir esta habilidad. Las empresas deberían implementar esta tecnología en un proyecto que pueda manejar el riesgo.
The amount of data that even a relatively low volume website can generate is huge. Once you add in analytics, business metrics, demographics, user profiles and multiple devices, it can become overwhelming. Many organizations use data warehouses as a repository with data being sucked in from all parts of the organization. The challenge here is that these often turn into “Data Fortresses.” Even getting timely business metrics becomes a challenge, let alone running exploratory queries across the entire data set. Technologies like the cloud based BigQuery help. The pay-as-you-go model and the ability to do ad hoc queries lets you gain insight without buying specialist hardware and software. A data-driven business should put data in the hands of the decision makers, not hidden behind technological barriers and bureaucracy.
EvaluarVale la pena explorarlo con el objetivo de entender cómo afectará a tu empresa.
Google’s BigQuery brings data analytics to the cloud. Rather than loading data into an expensive data-warehouse with predefined indexes, BigQuery allows you to upload and investigate a data set through ad-hoc SQL-like queries. This is a great way to create a cheap proof-of-concept or even a complete application, as processing of hundreds of gigabytes of data by thousands of servers happens in seconds.