The recent innovations have equipped organizations with high computing power, storage capacity, and development platforms required to achieve accurate predictive analytics.

FREMONT, CA: Data has emerged as one of the greatest boons of technology, especially for organizations trying to maintain a competitive edge in the market. However, the size and amount of data cannot contribute to the growth of the organization unless it is analyzed and turned into actionable insights. Hence, the ability of the organizations to draw insightful conclusions from the treasure trove of information will determine its level of success.

In this regard, predictive analytics has emerged as one of the most disruptive technologies of this era. A product of business intelligence (BI) and business analytics (BA), it is being adopted by various businesses to process data and bolster their decision-making process.

According to various studies conducted across the globe, many organizations face the problem of data quality. The utilization of multiple systems complicates the process of data harmonization. Hence, it is vital for organizations to facilitate adequate data preparation and analysis. The recent innovations have enabled organizations to equip themselves with high computing power, storage capacity, and development platforms required to achieve accurate predictive analytics.

The in-memory computing technology can enable in-memory data storage, allowing complex data transfer in a matter of seconds. The applications of predictive analytics are not only limited to business. For instance, it is also leveraged in the preventive maintenance of mechanical parts in the transport sector.

The emergence of big data has led to the generalization of predictive analytics. It works on the model of studying past events to draw predictions. The dip in the cost of storage and technical solutions has encouraged organizations to incorporate predictive analysis into their operations. It not only gives the expected outcomes but also equips the businesses with the necessary data to plan effective solutions. 

The dominance of social media and connected devices has facilitated the growth of structured and unstructured data, collectively termed as big data. The rise of artificial intelligence (AI), machine learning (ML), and data science have facilitated the use of predictive analysis by organizations to decrypt the vast troves of data and extract valuable information to draw forecasts on future outcomes and form appropriate strategies.