Big Data for small business – A practical approach

The emergence of Big Data in recent years, has amplified the complexity and demands on Business Intelligence systems. Does this mean that the potential operational efficiency improvements, customer intimacy, and competitive benefits associated with business intelligence and big data analytics have become even more inaccessible to small businesses that are limited by resource and expertise constraints?

“Business Intelligence (BI) has become a strategic initiative and is now recognized by business and technology leaders as instrumental in driving business effectiveness and innovation”. Many organisational BI initiatives struggle through a myriad of technology platforms, reporting tools and localized data sources that not only fail to deliver consistent information that can drive value-added and timely executives decision-making, but also expose the business to weakness in terms of data security, data access, data quality, and data scalability. In particular, the Small and Medium Size Enterprises (SMEs) that typify indigenous Caribbean organisations are often challenged by the complexity and resource requirements of traditional BI solutions. The design and implementing of the classical data warehouse architecture has proven to be technically and financially daunting for the average small business.

Does this mean that the potential operational efficiency improvements, customer intimacy, and competitive benefits associated with business intelligence and big data analytics have become even more inaccessible to small businesses that are limited by resource and expertise constraints? Fortunately the availability of a rapidly maturing range of open source technology platforms such as Hadoop and MongoDB and Cloud computing services such as Cloudera have made Big Data Analytics accessible and affordable to even the smallest organisations.

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