Story: How it All Comes Together

Having observed current trends –the tip of the iceberg–in Digital Transformation, now we dive below surface to take a look at the largersubmerged area of the iceberg: how Analytics supports the technologies we use at work and at home on a daily basis. We learn the many ways inwhich data is the new gold of this century.

Three main challenges

  • The exponential growth of data is forcing companies to invest in Digital Transformation to survive in the market. They face three key challenges: data quality, Data Governance and Actionable Analytics:
  • Data protection regulation requirements, which may be the opportunity to improve their processes to achive data quality.
  • Lack of skills and understanding of how to extract value from data, which can only be solved transforming the organizational structure for Data Governance.
  • Actionable Analytics which is the key to extract the most value from data: make it part and parcel of decision making.

The troubles within firms: “know thyself”

In the aformentioned areas firms are experiencing the following:

  • The need to take GDPR not as threat but as opportunity to improve processes.
  • A search for synergies between SMEs (small and medium enterprises) in gathering and analyzing data for the same purpose.
  • That lack of skills curtails their potential for Data Analytics.
  • How the Data Governance structure helps to eliminate data silos and establish standard procedures.
  • That the most promising strategies are:
    • Creating a strategy around data for a successful Digital Transformation.
    • Collaboration throughout the organization as a key for success in the use of data
  • How the CDO (Chief Data Officer) gains weight and needs to work together with the CIO (Chief Information Officer) to decide who handles what information.

Diminishing trust in automatic predictions for decisions involving big investments:

  • They need to understand the logic on which they are based
  • For that, they are working wih Agile Explainable Models.

Business Analytics Scenarios in 2019:

Of the four key trends for 2019:

  • Migration to the cloud
  • Embedded Analytics and Mobile Analytics.
  • The CDO (Chief Data Officer) will gain weight in the organization.
  • Making Analytics more

The first two are related to data quality, the third to Data Governance and the fourth to Actionable Analytics.

  • In order to overcome barriers to Business Analytics, firms should:
    • Take into account their business context to industrialize their Analytics capacity.
    • Base their decisions on data from sources such as social media (this is being Data Native).
    • Expand their data possibilities.
  • Embedded Analytics and Mobile Analytics, offered by Business Intelligence suppliers, will help:
    • Minimize maintenance and administrative work (usually the preserve of the CIO).
    • Increase agility.
  • Technology can help create solid processes to ensure compliance with the regulation in the long run, compensating for the time, money and resources it requires.
  • Work relentlessly to detect silos (areas or departments) of bad data…
  • Are using FAM (Friday Afternoon Measurement) to know their percentage of quality data.
  • With the appropriate infrastructure, data quality makes it possible to improve BDA (Big Data Analytics) and IoT (Internet of Things).
  • The interaction of BDA and a diversity of social media sources has a positive effect on the market, particularly for small and medium enterprises.
  • In 2019, businesses will introduce Governance to Analytical Models:
    • So they can aggregate the metadata around their models…
    • And ensure all teams have a complete understanding of their data to leverage it for insights.
  • Metadata can be the center of the Data Governance effort, as understanding the context of the data content is the central concept of data stewardship
  • Names and descriptions of the roles and responsibilities will be connstantly adjusted, depending on organizational culture.
  • The Chief Data Officer (CDO) is still on the rise.

What is to be done?

  • Understand the regulation to make the needed organizational changes in the best possible way.
  • Have a data layer that can sit on top of all their multi-cloud and hybrid cloud architecture.
  • It is important that firms conduct their own FAM (Friday Afternoon Measurement) study:
    • It is quick and powerful.
    • It is an opportunity to find out where they stand regarding data quality.
  • Agile operationalization of data pipelines, referred to as “DataOps, is as critical as the development process, in order to scale their total number.
  • Thanks to the fact that different lines of businesses were able to foster open communication, companies should broaden their Data Governance program and shifting their focus beyond just governing data.
  • Successful companies will follow a Non Invasive Structure of Roles and Responsibilities.
  • Analytics professionals should be the flag bearers of the conversion process of actionable insights into effective actions.
  • There should be a decision rule, rather than purely relying on it from an organizational perspective