Managing Data during and after Covid - 19

Political economist and sociologist, William Davies states “a crisis of such magnitude will never be truly resolved until many of the fundamentals of economic and social life have been re-created." Data architects and business strategists are struggling with extraordinary circumstances due to the onset of the COVID-19 pandemic.

New York, New York, United States, May 24, 2020 - /PressReleasePoint/ - Political economist and sociologist, William Davies states -a crisis of such magnitude will never be truly resolved until many of the fundamentals of economic and social life have been re-created.

Data architects and business strategists are struggling with extraordinary circumstances due to the onset of the COVID-19 pandemic.



Effects of the Crisis
The effects of this pandemic can be classified into three categories:

• Medical
• Social
• Economic 

The impact of the pandemic on the medical profession is quite severe and disturbing. However, for the purpose of this article will concentrate on the social and economic impacts
  

Data Strategies Affected by Social Distancing 

In spite of the evolving medical catastrophe, businesses have to examine trends, gain awareness, crunch numbers, and also finally make decisions. As a matter of fact, it is NOW that businesses actually need to make the best decisions with utmost urgency and extensive import which come with more risks. This in turn requires data of considerable volumes, which is well understood and is of the highest quality, delivered quickly and efficiently.
Most organizations over the past decade have created data supply and analysis pipelines with analysts and data scientists involved from the early stages of the data development. They work on premises, with the data being sourced from well-structured data warehouses and data lakes. There is a high dependency on the physical infrastructure which is a mix of powerful processing and remote or local storage connected using a highly secure network. This type of work requires workstations to be powerful and have more than one large visual display unit. Data is then modified, restructured, and then presented for analysis. The goal here is to create standardized data sets which can be easily accessible.
The ongoing social distancing and work from home norms being followed disturbs this procedure and shifts such processes to home offices through public networks which are highly unsecure. Thus, IT departments are challenged with software, hardware, security infrastructure and network capacity issues. Also, there are architecture and data strategy questions such as:

• Where can the data be stored? 
• Who is accountable for the governance of data and how can that be enforced?
• How can such multi-locational pipelines be created and managed? 
• How to address issues related to duplicate data and change synchronization?

Businesses having cloud centric data strategies will be better placed than those which do not. The sole reason for this being, cloud data is widely distributed and accessible.
The cloud centric approach does address the physical aspect; however there are still governance issues when sensitive data is widely accessible. The solution for such a challenge is a revamped distributed data design. Such a design should extend to the present data lake concepts and data warehousing while also accommodating wide data virtualization and classification

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Economic Impacts

The early estimate of the economic impact due to this pandemic suggests an even harder hit than that of the Great Depression during the 1930s. Business strategies will most likely resort to cost reduction and self-preservation across most industries. Focus will shift from forecasting customer satisfaction to improving production and sorting out distribution and logistic issues as the global supply chains have been highly disrupted.
A few implications for data architecture and strategies are clear already. Bring out more value from legacy systems and information investments which are already present. Expensive migration of data warehouses to the cloud need to be stopped. Only data lakes which are successful may stay on Hadoop. Unlimited streaming of entertainment videos may stop, to promote transport of data for real businesses. Patient management needs and disease tracking will have to be prioritized over privacy.



About Aretove Technologies

Aretove technologies is a Technology Consulting & Services company focused on Data Science solutions at the intersection of Business Intelligence, Artificial Intelligence, and Machine Learning. Aretove technologies began our operations in 2012 by building high volume online platforms. By leverage the expertise gained in Data Processing, Big Data, Machine Learning and help our Clients accelerate their Data Science, Business Intelligence, and Applied AI initiatives. At the core, Aretove still has a startup DNA and understand the urgency of time-to-market. We work in a collaborative mode with our clients to solve their complex data problems in the most efficient way.