The year 2019 looks promising, more than ever driven by Data. What are specifically the trends and topics to track? Here our videos to find out the answers with images: Organizational Strategy, Self-Service Data, Collecting data, Artificial Intelligence… Happy New Year everyone!
1. Organizational Strategy
Data is a company asset
Data is at the heart of any organizational strategy
It is an under-exploited resource whilst its return-on-investment is reaching record levels
In every sector, no-matter the size of the company, data is an important asset
As with all company assets, its exploitation requires expertise, governance and technologies
2. Self-service Data
Improve access to data in the company
Self-service access to data in the company, increases business value and decreases costs
Self-service addresses a large user population thanks to a combined approach of Data Prep, Data Visualization and Data Science
The internal and external data catalog enriches the information whilst establishing agile governance
Whilst companies prioritize access and usability of the data, businesses must be empowered and enabled to profit from its use
3. Collecting data
Acquire relevant information
Companies innovate to create connected devices and digital services which generate relevant usage data
It is the virtuous circle of data:
creating new services which generate new data
which permit to create new services
which generate new data
which permit to create new services
which generate new data
which permit to create new services
which generate new data…
GDPR establishes a regulated working environment for personal data which opens up countless processing possibilities
4. Artificial Intelligence
Deep Learning enters the company
Artificial intelligence is revealing itself to be as impactful as the internet
Deep Learning is one of the most advanced forms of machine learning
Fueled by data, deep learning applications are diverse: image analysis, natural language processing, task automation…
Technologies are currently available and already provide many services to the companies that choose to embrace them
5. Data Architecture
Take up the AI industrialization challenge
Information systems must evolve to support the eclectic uses of artificial intelligence
Real time, learning, maintenance or even scaling of complex algorithms are some of the technical challenges
The DevOps fundamentals such as containerization or continuous integration and testing, are to be applied
New architectures based on NoSQL, cloud and data virtualization is necessary to meet these challenges
6. Data Governance
The function becoming more professional
With compliance programs to meet mandatory obligations such as GDPR and multiplication of uses, data governance jobs are becoming more professional
Transverse governance is needed to maximize data usability together with guaranteeing its security and protection
Repositories, common language as well as data quality and data catalog are amongst the leading priorities
The Chief Data Officer formalizes and sponsors the role in companies with the key functions of Data Owners and Data Stewards
7. Artificial Intelligence
The essential ethical question
Artificial intelligence is profoundly changing our society and poses a series of ethical questions
The algorithms mimic our behavior and can induce cognitive bias rewarding perceptions more than reality
Complex, not based on specific rules, processes and results based on artificial intelligence are sometimes opaque
Adopting an ethical, fair and transparent artificial intelligence system is essential to its deployment
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