By Gil Nizri
The business world never rests. Once companies internalized that data is an asset, they started collecting it from anywhere – every second and in every situation. But after years of data collection comes the challenge: how do you use this data?
Quickly, everyone realized that the existing BI reporting systems, which presents data about the past, would not suffice. A leap would be needed into the new world of advanced analytics based on machine learning and knowledge-based analysis.
To meet this need, however, was easier said than done. Expertise and knowledge in this new field, until recently, was in the exclusive domain of a very small and elite group of people: data scientists. As such, the demand for data scientists skyrocketed and the business community became quickly and acutely aware that there was a shortage of data scientists. And, even if they could find one, he or she would be expensive and painstakingly slow at answering the pressing business questions of the executive team.
Could there – would there – be an alternative?
Data science for non-scientists
Enter the DIY data scientist.
The world’s leading consulting firm, Gartner, coined a new term in the analytics industry: DIY data scientist. This is a person that produces forecasting models, who uses advanced analytics, but he is not a data scientist and / or a statistician by training. Rather, he or she is given the science through an automation tool to deliver the results that his or her company needs.
Gartner recently predicted that by 2020, the number of DIY data scientists in the world will reach five times the number of data scientists. Citizen data science is emerging as one of the leading computing professions, and for anyone involved in BI, this is a real opportunity for a professional (and personal) upgrade by merging its capabilities and knowledge into this new and interesting job.
The BI developer is equipped with an in-depth understanding of business processes and has the knowledge and experience in retrieving data from the various sources of information stored in the organization’s data warehouses. The connection between this knowledge and modern predictive automatic tools produces a new, quality and necessary professional, with only a few hours of instruction.
DMway built “data scientist in a box” system, which simulates the knowledge and experience of a human data scientist but is accessible to the world of advanced analytics and BI developers and to organizational analysts who want access to predictive analytics and machine learning.
With the DMway tool, any BI analyst can make predictions. Using the tool does not require any prior knowledge in the world of machine learning or data science.
A quality prediction model that is no less than a human scientist would product
A quick model, delivered more than 90% faster than a human scientist, allowing immediate response time for business purposes
A more than 90% reduction in maintenance costs of the model
DMway customers use the platform for a variety of business applications, such as predicting customer abandonment, selecting optimal marketing value for the customer, improving service center performance, predicting consumer behavior, dynamic pricing, generating value from IoT data, machine downtime forecasting, and much more.
DMway has dozens of customers in Israel and around the world, including: Direct Financing, Yes, Ituran, Leumi Card, eToro and CNN.
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