Today's world is increasingly digitilized, and with 5G networks the promise is that not only people, but the most diverse devices will be connected. The amount of data that companies will have to manage only grows over time. But many companies do not realize they have a big data problem, or they simply don't consider it big data.
Failing to address the challenges of big data can result in the gradual increase of costs, as well as in the reduction of productivity and competitiveness.
An appropriate big data strategy can help companies reduce costs and acquire operational efficiency by migrating existing intensive workloads to big data technologies, as well as implementing new applications to take advantage of new opportunities.
Nonetheless, big data systems can be described not only around the data management challenges, but also in terms of the increase in volume, speed and variety of data, the veracity of the information collected, and the value they can add to organizations.
Those issues in general can not be easily solved with traditional databases:
- Volume: from terabytes to petabytes or hexabytes of data;
- Variety: includes data from a wide range of sources and formats, such as web logs, social media interactions, online and e-commerce transactions, financial transactions, mobile devices, sensors, etc.;
- Velocity: companies and users have increasingly demanding requirements, from the moment the data is generated to the moment when valuable information is delivered to users. Therefore, it is necessary to collect, store, process and analyze the data in increasingly shorter periods of time, which once were once a day and are currently in real time;
- Veracity: it has been very common to use data coming from less structured sources or not structured at all, or data that is uncomplete, inacuratte and/or unprecise. Categorizing and cleaning up that data so that it becomes reliable is a real challenge.
- Value: The value that can be extracted from the data also grows as the technology allows to expand from a descriptive analysis (what has happened and why?), passing through a predictive analysis (when and how will it happen again?) until you reach the prescriptive analysis (what should you do if "x" happens?).
In TruStep, we are able to help your organization to incorporate the latest Big Data system techniques and tools that today exists. Call one of our experts to discuss Big Data and understand how we can help you.
