Many organizations have been using Big Data to analyze huge datasets and gained visibility in to the data frequency and trends to perform predictive analysis for their retail sales orders or other business critical applications. Others have used it to understand how to identify and move specific data sets over to the cloud, and optimize consumption for the datastores that remain on-premises. The perceived and extracted value of Big Data depends upon the usecase that you have planned to use it for.
The typical workstreams involved in the Big Data discipline are as per below. In order to achieve business value, here are some questions to ask when working through these workstreams:
- • What are the different sources of data to bring in to the data warehouse?
- • Where are these data sources located?
- • How secure is the data coming in?
- • How accurate is the data from the incoming sources?
- • How will the data be brought in?
- • How long will it take to transfer all the data?
- • How frequently will data need to be synced or transferred in to the data warehouse?
- • What information is targeted to be extracted out of the data?
- • How frequently will jobs need to be run?
- • How complex are the queries?
- • What are the different types of data that will be analyzed?
- • Do the data sets need compression?
- • Is the volume of data exploding out of control?
- • Does the data needs to be compressed in storage, or during transfer, or both?
- • How are you visualizing the data today?
- • Do you have unified dashboards that present relevant information?
- • Does the data need to be collated and presented via different tools?
- • Can the charts be easily exported?
- • Will you be running real-time interactive queries?
- • Or long running batch processes?
- • Will the queries request additional compute resources on demand?
- • How will the data in storage be secured?
- • How will the data in transfer be secured?
- • How to make sure that specific roles can only access specific data sets?
- • How to achieve data isolation?
- • How to secure data against external threats?
- • Are there any regulatory requirements for the associated data?
There are many aspects to consider when you are building out your Big Data environment – be it on-premises or in the public cloud. Keyva can partner with you assess your current goals, and recommend a people, process and tools strategy that fits your Big Data needs.
Contact us today to get started with your Big Data initiatives.