Data are increasingly used to make strategic and operational decisions. According to research by Splunk and True Global Intelligence, eight out of ten companies consider data as very or extremely important for an overall success. All the while, almost one full half estimate that they would not be able to manage a rapid increase in the quantity of data, when 57 % of companies cannot even keep up on their current growth. Effective governance makes it possible then to be sure of their reliability and quality, and to use
them in a responsible and ethical way.
Beware, Dark Data!
Nearly one in two IT department heads believe their company does not fully get the challenges related to the rapid growth of data and 66 % of IT leaders indicate that the proportion of unused, unquantified and unexploited data (known as dark data) makes up more than half of their business data. In an interview with the HUB Institute, Robert Worsley, Head of Data & Analytics with Hitachi Solutions France, points out that several aspects contribute to cumbersome data collection and analysis. First off, data by themselves have “an ever increasing volume, a variety of shapes and formats. Moreover, they can appear and morph shape very quickly.” Robert Worsley continues, the skills necessary to process them make their processing more complicated: “One often talks about data engineers, data scientist, data stewards or even business analysts. The processing of some data or the application of certain strategies require additional qualifications that may be hard to obtain.” Finally, “a third element has to do with how the teams are organized. They must be "mixed-up" enough, that is, by bringing in staff with the required technical skills, but also integrating more business-oriented profiles so as to make sense out of the data.
The new tech careers
Data engineer: are responsible for the design, construction, maintenance and supervision of the data management systems. They must be capable manage the infrastructure for stocking, processing and analyzing the data useful for the data scientist.
Data scientist: use advanced statistical techniques for extracting information out of large amounts of data. They can foresee future trends and behaviors as well as collect, prepare, analyze and visualize the data.
Data analyst: they concentrate on analysis to understand trends and models through the use of base statistical techniques for resolving issues.
Data governance manager: they implement governance data, processes and policies for efficient management. They are the guarantor of the quality and must make sure that the confidentiality and security rules are followed.
Data visualizer: their visualization tools present information in a clear and easy to understand manner to help the deciders to make informed decisions.
Likewise, new processes see the light of day, such as data storytelling, a mash-up of communication and data science. Data storytelling is a data communication process using stories to transmit in an efficient manner important hidden data and thus make these data easier to understand, comprehend, more engaging and finally, more impactful. In an interview for LeBigData.fr, Charles Miglietti, the CEO of Toucan Toco, asserts: “Data storytelling fulfills this need for companies to have their data ‘speak’, as it were, so as to put in the hands of the final users, who are neither analysts nor data scientists, reports and graphics hewing to their activities and to their needs. Data storytelling, is what allows to give a clear vision of the key indicators of their activity to ensure an elevated adoption rate amongst newbie users.”
Data Safety and Quality
Safety and conformance requirements become ever more complex for IT department heads. They strive to implement security policies and procedures to protect data against external threats. Leak risks do not only concern the confidential data of the company, but also Personally Identifiable Information (PII). PII’s are data that can be used to identify a person in a unique manner (name, address, telephone number, e-mail, health information, etc.). These sensitive information are protected by data protection laws. Potential sensitive data disclosures can be due to security breaches, but also to open access to coworkers in bad circumstances. The success of remote work is, likewise, a threat to be taken into account.
As it is, almost 40 % of surveyed remote workers declare using unsecured personal applications to access to confidential professional information while, for their part, Gartner indicates that more than one on two IT heads foresee a new increase in remote work. In contrast, data governance allows the surveillance of the use of data for detecting potential violations and protect sensitive data by employing methods such as data segmentation, depending on their security level.
Some solutions propose a large degree of security measures. Power BI, for instance, allows classification of sensitive data, application of governance strategies, real-time monitoring or even protection strategies against data loss (Data Loss Prevention). Other tools bet on a unified governance such as Microsoft Purview which enables protection and to bring more visibility all the while identifying the regulatory risks. Different companies, such as IBM, OvalEdge, Truedat or Collibra offer their own solutions.
Regulations: what you must know
Data governance and regulations are closely linked. Governance must adapt to regulatory changes. In effect, public entities are more demanding through frequent changes. Like the GDPR [General Data Protection Regulation] in Europe, it is crucial to conform with the regulations in force.
Data Governance Act and Data Act: applicable as of September 2023, the Data Governance Act aims to improve data governance in Europe by creating a regulatory framework, facilitating access to companies and researchers, while protecting personal information and security. Regarding data regulations, the Data Act of the European Commission legislative proposal completes the dispositions for developing a single data market and ensure a better distribution of the value stemming from the use of data in regard, in particular, of the development of the Internet of Things.
GDPR: the guarantee of protection of personal data, a data governance is effective if it is considered within the GDPR framework. This includes the implementation of policies and procedures to watch over data or even the training of employees on data protection. Some organizations must, likewise, appoint a data protection officer (DPO) to monitor the RGPD enforcement and advise employees on data protection.
Hunting down the golden nugget
The speed at which companies create, update and distribute their information is constantly increasing. Companies therefore sometimes lack visibility regarding the collection of their data. Most of them are unable to effectively extract unstructured data and do not know how to interpret this information.
Unstructured data (emails, texts, images, videos or audio files) is information that is not organized in a specific format. Nearly 80%
of all business data is unstructured and therefore cannot be analyzed as is. So how does one turn this unstructured material into usable data? The answer is through Intelligent Document Processing (IDP) options. They use Artificial Intelligence (Machine Learning, natural language processing, deep learning, etc.) to convert, extract, classify and categorize the relevant data. Ensuring data quality is therefore essential to ensure that business decisions are based on accurate and reliable information. In order to control data quality, it is therefore advantageous to set up a data quality management process to validate, verify and standardize them.
Data governance, through its multiple aspects such as protection, quality, accessibility and ease of use, appears as an essential issue. It allows organizations to use data efficiently to extract maximum value from them. To establish a good governance strategy, establishing the right framework is essential to define and apply the policies that will support the management processes. Using powerful tools, effective data control and good visibility allow companies to improve their competitive advantage through accurate decision-making and better risk management while complying in full with regulations. Furthermore, the protection of consumer data is an evident sign of professionalism that contributes to build up the trust consumers grant to businesses.
Sources :
Allez au-delà de la gouvernance avec Microsoft Purview | (Go beyond governance with Microsoft Purview) | Microsoft Purview
Top IT Priorities: Leadership Vision for 2021 | Gartner
Stratégie européenne pour la donnée : la CNIL et ses homologues se prononcent sur le Data Governance Act et le Data Act (European Data Strategy: the CNIL [French National Commission on computers and civil freedoms] and its counterparts state their position on the Data Governance Act and Data Act) | CNIL
Une nouvelle étude révèle que, à l’aube de l’ère des données, le volume et la valeur des data augmentent de façon exponentielle (A new study reveals that, at the dawn of the data era, the volume and value of data increase exponentially) | Splunk
La gouvernance, un élément essentiel pour réussir les projets data selon Hitachi Solutions (Governance, an essential element for successful data projects according to Hitachi Solutions) | HUB Institute
Comment valoriser ses données grâce au Data Storytelling ? Interview de Charles Miglietti, CEO de Toucan Toco (How to increase one’s own data value thanks to Data Storytelling? Interview with Charles Miglietti, CEO of Toucan Toco) | Le Big Data
Principles best practices for data governance (PDF) | Services Google
Statistiques sur le télétravail (Remote Work Statistics) | Wrike
Protection des données dans Power BI (Data Protection in Power BI) | Learn Microsoft
Feuille de route sur l’adoption de Power BI : gouvernance (Road map on adopting Power BI: governance) | Learn Microsoft
Le guide de la sécurité et de la gouvernance des données (PDF) (The Guide for Security and Data Governance) | Salesforce
What is Intelligent Document Processing? | Metamaze
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