The Direction of Advanced Analytics today

Currently there are lot of confusion in the market regarding machine learning (ML), natural language processing (NLP), and artificial intelligence (AI).
There is a lot of excitement in the market about artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). History tells us that these technologies has been around for some time. However, with new algorithmic developments making these technologies more attractive to individuals (such as data scientists) and companies. The adopters of AI are embracing the advanced analytics technologies for a number of reasons including improving operational efficiencies, better understanding behaviors, and gaining competitive advantage. These competitive advantages is widespread to provide quick and efficient development in industries that include commercial, hospitality, etc.

Organizations are making use of these technologies in numerous ways. Some are applying machine learning for traditional use cases such as risk analysis or analyzing educational and commercial applications. Others are using machine learning for cases such as preventive maintenance.

Data science is picking up in the commercial, hospitality and other industries. The data scientists are leading the way in terms of model building using various technology approaches. They are making use of open source analytics technologies such as Big Data, Hadoop, Python and R as an important part of the advanced analytics efforts. Companies continue to build out their data environments for analytics. This is being carried out in different platforms that the company choose, and they are getting interesting and adventurous in the approach.

It is getting interesting that more AI technology approaches are aiming on users and competitive companies. It is not unusual that analytics applications include Artificial Intelligence (AI) and Machine Learning (ML). The AI and ML algorithms are being coined to provide insights to the analysts that eventually benefits companies and individuals targeted. The areas that are being explored include natural search processing (NLP). is using this approach in the cloud analytics application. is using data scientists to focus on data quality, system analytics, and operations to provide quality analytics that will benefit the users for Based on observation and research, it is obvious that organizations are gaining value utilizing analytic technologies. This is good news! The earlier organizations adopt the analytics the better. Based on research there is learning curve that give benefits to the earlier organizations adopters.

You may want to take a look at to benefit your company or organization. organization have analytics expertise to help your organization succeed. Just try it!

Archie Addo, PhD
Senior Data Scientist,

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