Data-Analytics-Myths-Busted

Data Analytics Myths Busted

  • 03rd Feb, 2017

Data Analytics is sold as a silver bullet by product and integration service companies. It is perceived that to make use of data analytics, your organization will have to invest in expensive tools and set up a complex infrastructure. To support that infrastructure, you need to set up a dedicated IT team. Is this really true? If so, it might be out of reach for many organizations, especially small and medium enterprises (SME).

Let’s bust some common myths that have been created by companies selling the tools and services.

You need Big Data in order to start having analytics

Most analytic solutions are sold as requiring setup of enterprise data warehouses, data marts, and expensive data visualization tools. The fact is that you can do data analytics with as little as information in a spreadsheet. You don’t need volumes of data to get started with analytics. Start with the information you have. Analyze and start investing in data collection where it makes sense for your business. Over a period of time, as you collect more data, you can start with setting up data lakes and move on to analytical tools that integrate well with such data sources.

You need a dedicated IT team to do analytics for you

The next aspect of analytic solutions being sold is to setup dedicated IT teams to support the infrastructure and analytical reporting needs. In fact, analytics should remain a business function. IT should not be generating analytical reports for you. It defeats the purpose, because you are restricted in the way you want to slice and dice data to extract the information you need. As already mentioned, your infrastructure and choice of tools should match the information you have today.

Data Analytics is an “exact” depiction of trends

It is a common myth that data analytics should only be conducted over 100% data. For example, if you are trying to gauge customer satisfaction for your products, you don’t need to collect feedback from each and every customer. It would be great, but not mandatory. Data analytics is meant to be predictive and indicative of trends. Trends can be on smaller samples of data and can be fairly accurate as long as they are randomly collected. The real benefit of data analytics is in how quickly you can identify a trend. The longer you have to wait to collect data, the more out of sync your organization will be with the trends.

Conclusion

Data analytics is a critical tool in decision making. It is important to involve business intelligence consulting services who can guide you on what tools and infrastructure you can use to start data analytics. However, you are the owner of what kind of analytics is required. You should control that aspect. Lastly, but not the least, data analytics benefits most when the results are available in a short turnaround time. If you take weeks and months to collect data before analyzing it, your business may lose out on critical opportunities.

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