New Enterprise Data Model

The account data that was initially loaded must be kept in the new enterprise data model. This richness takes the form of manipulating legacy account records by adding data, changing data, and possibly deleting data. The adoption of data is done in the following order in descending order of priority. Extract data from CODA and drive dolphin extract. This extraction is based on a set of initial rules provided by the business.

Within the company: By using block chain technology, you can reduce the cost of auditing your own data by integrating data from various branch offices and share it with auditors. Using this new data, an enterprise can build an artificial intelligence model, for example, to predict customer confusion over models previously built only in regional offices. What is the "data mart" of each regional office? Within the ecosystem: Competitors (such as banks and music brands) never share data traditionally. However, it is possible to show directly how to develop a better model for credit card fraud prevention through comprehensive data from several banks. Or, for supply chain organizations sharing data via block chains, we can more clearly identify the root cause of later stages of failure in the supply chain and process old data in the supply chain using AI I will. For example, where is E. coli strain displayed?

In the modern supply chain, continuous design processes based on the latest data are required to make the design model vividly express the supply chain. Data Guru builds a repeatable data conversion workflow that connects users directly to the system running the enterprise and updates the model data. Integration with LLamasoft's supply chain design tool allows users to automatically build and run supply chain models. "Our approach to business development means that data is everywhere.DataGuru can connect, get data, clean up, adjust to the appropriate level, and extract data to Tableau It is a very good framework for Data Guru, so the biggest advantage of Data Guru is that you can save a lot of work by pressing a button, so you can spend a lot of time analyzing your data. "

"With Data Guru you can shorten model construction time by integrating data extraction and modeling processes so that you can extract data more efficiently by connecting directly to the data source."