Pairing Big Data With AI for Your Business

How Using Big Data and AI Will Improve Data Management

Data analytics is a powerful tool, one that has already had a major impact on countless businesses and industries. With even more changes expected in the days ahead, understanding the evolving role of analytics has become an important concern. The relationship between data analytics and artificial intelligence (AI) is often much closer than many people realize. AI and other technologies that have the potential to help unlock the full potential of data analytics may play an important part in shaping the world of tomorrow.

Data Collation and Collection

In order to be effective, analytics requires access to the highest quality data sets possible. AI may be able to pull data from a wider range of sources and organize in ways that may be far more effective and efficient than would be possible through use of contemporary methods. From smart devices able to automate data generation to sophisticated AI and machine learning algorithms that may identify the potential value of data that would have otherwise gone overlooked, next-generation data generation, collection and collation methods are poised to create nothing short of a revolution within the field of data analytics.

Multiple Analysis

While the best human operators may be able to analyze a data set in multiple ways, enhanced automation is soon expected to become the industry standard. Skills training resources, such as an Apache spark tutorial, can provide human operators with the ability to better utilize the latest tool, features and solutions. The ability to conduct a more comprehensive analysis, run through data sets multiple times or to assess different aspects of the records and information on file at the push of a button promises to be a real game changer. AI is expected to provide enhanced automation that will allow almost every step of the analysis process to be completed with greater speed, ease and often with superior results.

Structuring the Data

Attempting to analyze and assess data in order to identify any underlying patterns can rarely be done effectively in a single pass. AI makes it much easier to structure data more efficiently and to reassess and reanalyze as many times as needed. AI can also be a powerful tool for reordering data sets in less conventional ways. Restructuring data in ways that may seem counterintuitive or finding patterns by comparing divergent entries and seemingly unrelated data may allow for more frequent and significant breakthroughs to be made. Analysis methods that rely on conventional data structuring or that may be limited in terms of the scope of analysis available may soon become obsolete.

Identifying Underlying Patterns

A popular adage pertaining to AI is that machines do not need to be perfect, they simply need to outperform their human counterparts. While the human brain has evolved to recognize patterns, it also suffers from set limitations that AI has recently begun to supersede. Automated data analysis has the potential to deliver a level and quality of results that are simply not available through conventional methods. AI has begun to routinely outperform human doctors in efforts to identify and diagnose a growing range of diseases and medical conditions, offering an exciting glimpse into the technology, solutions and changes that can soon be expected within other industries.

The Future of Analytics

Big Data can be expected to play an even bigger role within the world of business in the days to come. Other resources like AI which have the potential to revolutionize how we think of work, can help to enhance the effectiveness of data analytics ensuring that superior insight and greater understanding can be had by all. Each new development within the field of machine learning may help to unlock the full potential of data analytics by providing even the smallest companies, operations and organizations with the quality of results that are currently enjoyed by only a select few. Enhanced automation has the potential to allow for new analysis methods and to ensure that the impact data analytics will continue to be felt for years to come.