#Big data analysis consulting how to#
When collecting another data set, we will test the related assumptions to make the right decision on how to move forward.
Testing, measuring and learning - are crucial in the big data analytics process. Therefore, data-driven decisions should be present at the company at all levels: product development, pricing, marketing, operations and HR etc. In this way, you will have enough time to adjust your operations and understand how to use the data.ĥ) Connecting the clients’ data to your company’s processesĮvery data set you gather provides your company with an opportunity to improve the your services or products. The next step is incorporating new data hubs one by one.
A customer gets a coupon for a discount and is happy to visit your place.
Let’s say, if you are leading the retail chain, we can collect the data with the help of digital coupons. It is possible to build and deploy data lakes using cloud or on-premises infrastructures using dedicated tools such as Hadoop, S3, GCS or Azure Data Lake.ģ) Connecting data sources to your clientsĪfter deciding on data sources and storage, we connect them to the needs of your clients. Unlike a data warehouse, a data lakes implies a flat architecture for storing the data in its source format. A data lake is a repository for storing both structured and unstructured raw and processed data files. To reduce sotrage costs data is stored in so-called data or delta lakes. After that, our team will prioritize and evaluate them during this stage.Ģ) Identifying current and potential data sources
#Big data analysis consulting full#
It is not enough to start with already existing data, to use full potential of big data you have to identify additional data sources that can be used to collect structured & unstructured data. To deal with this challenge you need a reliable big data analytics strategy.ġ) Identifying current and potential data sources However, it won’t be able to play its role unless it is identified, gathered, managed and analyzed.