The notion of data governance and the value it can bring to businesses has a long history. In the early 2000s, it consisted of a loosely defined set of processes for managing large amounts of data and was clearly identified as part of the responsibilities of the IT department. From the moment e-commerce and social media began to develop, followed by the arrival of Big Data , companies began to realize the value of their data assets and became increasingly reliant on them in decision-making. With the evolution of more advanced ERP technology, data governance transformed into a set of practices that affected the entire company, as it became increasingly clear that different groups within the organization could obtain value-added insights from the same set of data, and that a company can obtain considerable value from reliable information flowing to the right person at the right time.
Fast forward to today and data governance is high on the priority list of any azerbaijan number screening company that manages and processes large volumes of data . Here are the reasons:
Survival in the face of accelerated digitalization
As ever-widespread digitalization gains momentum, companies’ ability to manage and leverage their data is now a key game-changer.
Digital transformation: In the era of Covid-19, the rapid implementation of digital transformation means that in 2021 companies must move quickly to be able to effectively structure and take advantage of the strong growth in data. 63% of business leaders say that Coronavirus has caused their companies to take on digital transformation sooner than expected (according to Celerity data).
By 2023, 75% of all databases will be in the cloud
The cloud: Cloud migration is also accelerating as organizations need to collect ever more data, distribute it in real time to an expanding audience, and strive for greater agility in their own data processing capabilities. In its “Our Top Data and Analytics Predictions for 2019” article , Gartner predicts that by 2023, 75% of all databases will be in the cloud, increasing the complexity of data governance and integration.
Personalization: 40% of marketers say their biggest challenge in personalization is linking different data-related technologies, while 34% say poor data quality is the biggest problem (Experian).
To be able to meet the future challenge of personalizing 360-degree consumer experiences, incoming data will need to be managed in a way that allows organizations to rely entirely on a data-driven decision-making process. This requires optimizing internal data policies, as well as adapting corporate culture, organizational structure, and technology infrastructure.
Handling the diversity of data types and formats
With over 20 billion IoT devices active in the technosphere, data diversity and disparity is increasing at an accelerating pace. As a result, different types of data and databases are spanning a range of storage locations – on-site, off-site and SaaS – that often have incompatible storage characteristics.
Therefore, it is critical to have effective data governance, security and recovery practices in place.
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Taking advantage of the exponential increase in data volume
Data volume is also growing exponentially, with the World Economic Forum estimating that 463 exabytes of data will be generated globally every day by 2025. The need to extract value from data as part of digital transformation initiatives means that the volume and complexity of data stored will only increase. Analytics-powered data governance programs will be more essential than ever to enable the storage and use of new data sources from increasingly advanced mobile technologies and platforms.
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