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With massive IT infrastructure deployed across organizations, IT systems generate enormous data through operational activity every minute, every day of the year. Key data variables involve – user responses, application performance logs, error messages, incomplete loops and much more. Most IT managers might look at this data explosion as a possible catastrophe in the making, overlooking the huge analytics opportunity this data provides. Utilizing advanced Big Data analytics solutions can help IT managers mine this raw data into meaningful insights for better performance of IT systems and enhanced design and development of future applications.
Big Data analytics can be used to build an adaptive system which is more proactive and can learn from the data being generated to help fix IT issues in a timely manner.
Not that this has not happened in the past. Traditionally data warehouses have used historical data to predict future trends or issues but with big data analytics we can predict more accurately and utilize structured as well as unstructured data points to monitor changes at a more complex level.
Also referred to as the data lake architecture, this solution not only permits us to derive insightful information but also helps us inculcate real time newer insights into our existing processes.
The biggest advantage that this newer analytics solution provides is that we can analyze structured and unstructured data sets together yielding improved insights, better predictions and hence reducing downtime and errors in the future applications being managed by IT.
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