IBM organized a data summit on March 15 in this year. Motto of the organization is plan, manage and optimize. Both their partners and they-selves get on the stage and share their experiences. The impression I got is that the company mainly adopts to go into (or carry on) partnership with large sized enterprises. The firm focuses on-premise cloud services as well as remote cloud. Products appeal to particularly finance institutions or banks because legal regulations enforces these institutions to work on on-premise cloud services.
Yesim Ozturk (IDC): Data-driven World’s Today and Future
- Transforming information technologies to business aims to optimize whereas digital transformation aims to create new revenue flow.
- Big data technologies already provided improving customer service and support and gaining customers.
- Currently, we are using these technologies to manage business operations and risk.
- We plan to use big data to create new businesses and improve our marketing skills.
- Still we have difficulty about data accuracy and extracting correlations between data
- Data ethnographers and data scientists would play more active role in 25% of enterprises until 2021.
- 50% of enterprises would create revenue from data as a service until 2018.
- Data retrieved from public resources would be stored in blockchain until 2021. In this way, public data can be verified.
Serdar Yilmaz (Chief Data Offficer of Isbank): Human to Machine, Machine to Human
- Intelligence and neuron numbers have correlation. Neural networks schemes are not different than we have in 90’s. But now we have power to calculate million times wider synapses.
- We prefer to use technology in life instead of sentence as a principle.
- We also locate the AI as a supportive of employees instead of they selves.
- Framework choice is one of the most important subject because gifted employees are limited. Gifted one should adopt the framework.
- Failing fast is better than failing.
- Dialog banking term covers both text based bots and voice bots.
- Put your potential projects on a 2D graph. We’ve put x-axis to ease of implementation, and y-axis to business value. You can choose different dimensions. You should follow common data between use cases. Suppose that use case 1 and use case 2 have same business value but implementation of use case 3 is harder than use case 1. If both use cases use common data, then use case 3 would be easier than you think. Then, you should prioritise use case 3. Because almost 80% of time cost is preparing data for AI projects.
Kivanc Uslu (IBM)
- IBM proposes a single infrastructure for AI transformation.
- Different roles such as Data Scientist, Data Engineer, Data Analyst can work on same environment with Watson Data Platform
- IBM Data Science Experience adopts both open source projects such as tensorflow, additionally its own intellectual properties such as SPSS.
- We also offer hybrid data management. You can work on both remote cloud or on-premise. This is important for finance institutions. They must not work on remote cloud because of legal regulations.
- Data scientists are people who dance with data.
Deniz Onay (IBM): Making Data Simple and Accessible
- 80% of world data has not yet been accessed and analyzed.
- We are going to a new world. There would not be neither software nor hardware. There would be (data driven) solutions only.
- No matter where data is stored. Cloud or on-premise.
- No matter its storage type. Sql or no-sql.
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