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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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