Today, a huge portion of business data is dynamic and based on activities occurring in real time. This data is either cataloged as time-series data or available as event streams (via web services). Here, it becomes essential to leverage real time tools that provides insights on what’s happening,
More importantly, each tool must be focused around answering a specific set of business questions.
Did something strange or out-of-the-ordinary happen in a signal stream?
When did it happen and how did it affect other metrics?
How do I exclude the noise of sudden activities in my business signal?
Can I see a overall seasonal patterns more clearly?
What is the overall rise or decline in my business measures over a specific period of time?
How does this compare across multiple time periods?
Can I see if a pattern of values for a business metric appears multiple times in a data stream?
Can I extract data that meets a certain set of range criteria?
How do business sub-activities contribute back to the overall
performance over the period of 1 year/ 6months/ Quarters?
Did a similar pattern occur in the past? Is the activity subject to seasonality?
Is there an easy way for me to see how much time it took for one activity to trigger changes in another?
Why Should I Hire Pykih? (PDF) to learn why we’re the smart choice.
Portfolio of work done - for Content Marketing (PDF) to see some of our past work.
Portfolio of work done - for Decision Making (PDF) to see some of our past work.
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