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Splunk has been a trend in the industry for quite some time, but what do we know about its use and the market Splunk is targeting? Splunk comes from the word “spelunking”, which refers to the activities of locating, exploring, studying and mapping.
- Data indexing: Splunk collects data from different locations, combines them and stores them in a centralized index.
- Using indexes to optimize searches: The use of indexes gives Splunk a high degree of speed when searching for problem sources
- Filtering results: Splunk provides user with several tools for filtering results, for faster detection of problems.
Let’s take a concrete example from the open data of the site “montreal.bixi.com” formatted as follows: Start date – Start station number – Start station – End date – End station number – End station – Account type -Total duration (ms)
With this data, we are able to find the most common routes, estimate the average duration of a trip, the anchorage points most requested for the entry or exit of bicycles.
For the operations team of the service, this provides real-time or predicted for the next day which anchors should have more bicycles, and mostly where these bicycles will go. They could predict the lack or surplus of bikes in the anchor points. If data is collected in real-time, alerts could be issued to indicate potential shortage or surplus in the anchor points.
Thus the system facilitates planning and allows to be proactive to meet demand, rather than reactive. We would even be able to detect an undelivered bicycle; for instance a bike that has not been anchored for more than 24 hours could issue an alert, so the operations team attempts to trace it.
For marketers, one might think this data is useless, while the opposite is true; the same data can be used to put in place potential offers to attract customers, since we have the data that give the time of departure and arrival, time of use of the trips, and the most used routes. One can thus know the most used time slots and make promotions or adjust the rates according to objectives of traffic or customer loyalty.
For the management, open data unfortunately does not give the price of races according to the status of the users (members or non-members), but the beauty of Splunk is that one can enrich the collected data with data coming from a third-party system, a database or simply manually collected. Management could then obtain reports and dashboards based on various factors, such as user status, travel time, days of the week, and much more. We could even make comparisons with previous months or the same month of the previous year. The applications are virtually limitless with data that resides in Splunk: the only limitation is that of our imagination!
These are of course fictitious examples made with available open data, but which could be real with your own systems and data.
The collection of information from a website can provide visibility for all users of a company, operations receive system overload alerts, marketers get information about the origin of the connections to target their campaigns based on this data, management gets a view of the user experience, as well as performance metrics that confirm SLAs.