Big data analytics has evolved to be the most promising technology tool in recent times. Across industries, big data and analytics are helping businesses to become smarter, more productive, and better at making predictions. According to a research conducted by the International Institute for Analytics (IIA), about 71% of the firms surveyed actively use analytics in everyday decision-making, or have plans to do so in the near future. While the adoption of big data analytics is on the rise, a lot of companies which plan to venture in this area ignore things which later become a bottleneck to their business plans.
We have listed some of the challenges which need to be considered while mapping out a big data and analytics strategy.
Data Selection and Integration
Organizations are required to select, structure and validate the raw data for analysis. The data would come from various sources and may not be similar in structure. There are numerous sources which generate terabytes of data in different forms. With such variety, the challenge is to manage and control data quality to meaningfully extract insights. Here, the most crucial decision making comes into the picture. The selection and structuring of raw data source do have a direct impact on the results generated for the analysis. If there are some loopholes in the selection and integration of data sources, then it may turn out into the failure of entire analysis.
Get it done in Right Way with Right Talent
Big Data is not everyone’s cup of coffee. It takes exceptional analytical and decision-making skills to be a fruitful data analyst. The desired manpower can be taken on board by the organization itself or, it must seek to a highly paid helping hand from the external consultants. The input investment must be reflected in amplified revenues and improvise the business control.
The analysis plays around with millions, trillions of data. The error proof handling of such a big volume of data has to be accomplished with well-built IT Infrastructure. Here also, you have two options either to invest in own infrastructure or to host all the processes with the infrastructure of the external service provider. It is well suggested by the studies to go for own infrastructure as it will offer many other benefits of sole proprietorship over the other option. Also, storing the analyzed data is a point of crucial consideration in IT infrastructure. But, at the end of the day, size of the business and targeted results will be the deciding factor for selection of infrastructure.
Protecting Data from Malicious, Privacy Thefts
There is always a theft issue associated with any type of digital data. Many advanced encryption tactics are there to help you out, but thieves are always a step ahead to hit their goal. Thus, data privacy and security strategies have prime prominence when planning for big data implementation.
Patience is the Key
Big data with deep analytics is a journey that helps organizations to glean useful insights and solve a business problem. Organizations need to understand that the data will grow and it is kind of an evolving process. Also, the analysis will remain at a platform for further reference and will help to get optimized results in other similar projects. Patience and belief are obligatory to get the ripen fruit of the big data project if embraced.
Big data analytics is taking the world by storm. IDC predicts the worldwide revenues for big data and business analytics (BDA) will reach US$150.8 billion in 2017, an increase of 12.4% over 2016. Big data analytics has ended in much simpler ways, for organizations to get an insight of their business functions. However, the use of big data analytics to the best of its capabilities sometimes becomes challenging. The prime confronts depicted above will surely help organizations to chart out successful big data and analytics projects.