#advancedanalytics

Key benefits of Advanced Analytics

The main purpose of advanced analytics is to improve data analytics, data sharing and business intelligence. To do this, advanced analytics uses machine learning and natural language processing. Using this tool gives companies the ability to make better decisions, provides employees with greater access to analytics and company flexibility.

Key benefits of advanced analytics:

  1. Flexibility of the company

The transformation of a company into a data-driven company is possible with clean and high-quality data. However, the data cleansing process can take a long time. Advanced analytics platforms are able to clean, combine and transform data from different systems in a very short time, and provide data quality reports. This helps accelerate future digital transformation projects;

  1. Expanded access to analytics

With the help of advanced analytics, the system becomes more convenient and comfortable for users, as well as more accessible to more users. Often, only a specific business analyst team uses business data for reporting purposes. Advanced analytics allows to expand this access. For example, the ordering department has access to analytics that previously only the finance and accounting departments had access to. This, in turn, will allow for analysis and increase customer satisfaction according to various criteria;

  1. Making informed decisions

An effective decision can be made based on qualitative data. Many leaders understand this and are moving to a data-driven approach. By doing this, they increase the demand for access to data and analytics. However, other users may also use the data to make decisions in accordance with their position in the company and responsibilities;

  1. Speed up the decision-making process

Advanced analytics eliminates the various manipulations and tasks with data that were previously performed by humans. This significantly saves time and speeds up the process of making an important decision;

  1. Cost reduction

The combination of artificial intelligence and machine learning ensures complete automation of the process. So, tasks such as processing data, cleaning it and joining it into a table to create reports that were previously performed by a person are automated. The rate of obtaining information is much higher – the user receives data in real time. In the long term, the return on investment in 3-5 years will exceed the initial investment by 30-50 times. Advanced analytics contributes to a more dynamic and efficient business development.

More analytics – more possibilities

Data and analytics are the main tools of the modern business in the digital world. Trend of additional data and analytic decisions searching is actual currently. Organizations demands are growing, they want to find one technology for satisfying most of their requirements. It was a reason for advanced analytics developing.

Despite visible benefits of modern technologies usage, some companies stay away and don’t understand how they can use them. It’s mistaken opinion that advanced technologies are applicable and useful only for major companies like Google, Microsoft, IBM etc. Another one barrier is investments required to technologies implementation into the enterprise. Advanced analytics is a decision of such questions.

What is advanced analytics?

Advanced analytics is the combination of technologies (machine learning and analytics) for automatization of whole data pipeline (from data processing to results generation). It could be compared with an umbrella that includes many disciplines and has high use. Such kind of analytics is used in all business areas for events forecasting. For example, advanced analytics in marketing is used for understanding customers’ preference and their behavior changes.

Gartner describes advanced analytics as autonomous or semi-autonomous data examination with the help of sophisticated techniques and tools, that promotes deeper understanding, more precise predicting and recommendations creating. It gives a possibility for companies to perform calculation like «what if», that are used to forecast trends, events and behaviors. Advanced analytics is comprised of such areas as artificial intelligence, predictive analytics, data mining, data visualization, semantic and graphic analysis, neural networks etc.

Advanced analytics advantages:

 Applications of advanced analytics in business

  1. Right data gathering

Data is the bases of digital era. In consequence of analyzing and coming up with data-driven answers business processes became easier. It gives an opportunity for management to make different decisions easier and more efficiently. But the main task is to identify and collect the right data. Advanced analytics give a possibility to correctly identify necessary qualities and make them operational for goal achievement.

  1. Creating business-model to optimize results

Business-model creating comes from capabilities definition. Here data mining technology is actual.  This tool allows to make a lot of tests that will help to identify submerged patterns. However, a result will depend on how efficiently executives can use received information. Advanced analytics is a perfect assistant in this task and creating of business-model according to the working system.

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