With the ever-growing amount of data produced each year, effective data management is becoming a key part of running a business. In order to establish a robust and effective framework for data governance, companies and organizations around the world rely on several cloud data management pillars. Let’s explore each of these key principles and their role in maintaining a safe and efficient cloud data framework.
Table of Contents
What Is Cloud Data Management?
Before we get into the main principles of cloud data governance, we first need to understand what data management itself entails. Data management or governance framework refers to a complex program that companies and organizations implement in order to ensure the quality, compliance, safety and effective management of all their data assets.
Unlike the more traditional data archiving methods, cloud-based data management systems feature full data integration, unifying all the data sources across the tenure enterprise. As data accessibility is key for running efficient operations, having a single point of control over all the resources deployed on the cloud becomes increasingly valuable. This is precisely what makes cloud data management a very appealing, if not a necessary, data storage solution.
Different companies and organizations will have specifically designed structure and cloud archiving solutions, directing the implementation of protocols and guidelines for data storage, usage, and management.
The Four Cloud Data Management Pillars
Now that we understand the basics of cloud data management, we are ready to explore the principles on which the entire framework is based. Specifically, the core cloud data management pillars include:
- Data strategy and governance
- Data quality
- Data standards and compliance
- Data integration
Data Strategy and Governance
For us to use the data backup on the cloud, it will first need to be readily available. This is where data governance comes into play. Data governance or stewardship ensures that the cloud data is available in a usable format to the right people and at the right time. For example, when it comes to sharing personal data about individuals from the EU, the framework needs to comply with the General Data Protection Regulation (GDPR).
Effective data governance is also necessary to drive successful data strategy. The best suggestions for managing extensive data transformation is the following:
- Obtaining executive sponsorship to set up data governance and strategy with the proper power.
- Assembling a cross-functional team for data governance consisting of application developers, data stewards, data architects, data analysts, and business users and analysts.
- Building robust governance frameworks that take proactive monitoring, frequent data reviews, and data stewardship into account.
- Establishing procedures for the evaluation and approval of data items and defining data stewards for different business areas.
A cloud data management framework with a well-established strategy provides an abundance of benefits – it improves efficiency and ensures compliance with all the industry standards. Last but not least, eliminating unnecessary duplicate efforts across different departments ultimately reduces operational costs.
Data Quality
Although businesses and organizations collect countless points of data during their operations, it doesn’t necessarily mean that the collected data can be used. The degree to which certain data is usable is known as data quality. This pillar is defined by four different parameters:
- Accuracy
- Completeness
- Relevance
- Timeliness
Only data that is “fit to use” will serve the company and its operations. In order to derive accurate insights and make the right operational decisions, it’s crucial to ensure high data quality. In regards to this core pillar, managing cloud data would entail defining clear data standards, implementing appropriate monitoring and reporting mechanisms, as well as establishing clear data validation and cleansing processes.
Poor data quality can have detrimental effects on your operations, including financial losses or organizational failure. Let’s take marketing, for example. If customer data is incomplete or inaccurate, your marketing campaigns likely won’t perform well. On a similar note, if you don’t know which products are selling and which are not, you may end up without items in stock, potentially losing profit. Luckily, you can avoid this by implementing a Data Studio SEO report template that will provide valuable data analytics, helping you track your user engagement.
Data Standards and Compliance
Data compliance standards, as well as a variety of international and domestic laws, define and affect the way companies and organizations interact with data during their operations. In order for the data to be collected, processed, shared, and used in any way, it needs to follow specific data standards. These standards may vary significantly between countries and regions and may be specific to any given industry.
Security is one of the top priorities when it comes to managing cloud-based data. As mentioned earlier, the GDPR affects the way data from the EU is shared (even outside of it). The Payment Card Industry Data Security Standard (PCI DSS) is an information security standard that clearly defines how merchants should use credit card information from big card brands.
Life sciences and industries also implement a variety of standards for data archiving and data backup, ensuring privacy and fair use of personal medical records. Data standards also define the format in which the data will be reported, creating universal methods of data recovery, archiving, and backup, as needed. Ultimately, data compliance ensures unhampered operations by minimizing the chance of legal repercussions due to unauthorized data usage.
Data Integration
As the final pillar of cloud data management, data integration represents the process of unifying the data from all the different sources across the enterprise. It essentially creates a central depository or “master records,” making your entire database easier to manage. A variety of data management processes, such as data recovery, would be significantly more time-consuming without cloud integration.
Businesses and organizations with well-integrated data frameworks are able to make better and faster decisions regarding their operations, ultimately gaining a competitive edge on the ever-crowded global market.
Benefits of Effective Cloud Data Management
While we have already gone over quite a few benefits of effective cloud data management while describing all its pillars, at its core lies data integrity and consistency. It harmonizes disparate data sources, which fosters interoperability among systems and establishes the governing framework needed for data quality maintenance. Other notable benefits include:
- Cost efficiency – Cloud providers operate on a subscription or pay-as-you-go pricing model, which significantly reduces upfront costs associated with hardware and infrastructure. Unnecessary spendings are also reduced, as many providers offer cost management tools.
- Scalability – The flexibility and speed of cloud-based data systems allow you to easily scale your data processing needs based on changing demand. Businesses can respond and accommodate their operations to high traffic spikes and ensure a smooth user experience without having to invest in a large permanent infrastructure.
- Accessibility and collaboration – Unlike a localized database, having all your data on a cloud only requires an internet connection. Making the data more accessible also encourages data sharing across the organization, which fosters collaboration between different departments.
- Security – Cloud data storage is more secure compared to on-site solutions. Data protection is achieved through limited access controls and varying levels of encryption, while data standards ensure compliance and alignment with international standards and regulations.
- Advanced data analytics – Besides having all the data at a single access point, cloud management also provides a variety of tools for data analysis. This provides insight needed for fast, fact-driven decision making in a competitive environment.
Image (Source: AdobeStock) Alt-text: An illustration of a collaboration occurring on a cloud
The Importance of Cloud Data Management
Recent statistics show that there will be around 200 zettabytes (a billion terabytes) of data around the world by 2025. As concerns about cybersecurity and data confidentiality continue to grow, having a well-defined cloud framework infrastructure becomes paramount. Data also shows that 94% of businesses have seen improvement in their security after transitioning to cloud-based systems.
In today’s crowded market, where data accessibility and cloud email archiving are becoming more important, enterprises with efficient cloud archiving solutions will have a competitive advantage. While these frameworks will vary from industry to industry, building a structure in line with the core cloud data management pillars will ensure data security and an overall more efficient operation.
Maximize the Potential of Your Cloud Data With Effective Management
As businesses across the world continue to adopt cloud-based systems for data storage, learning how to properly manage data has never been more important. While building an effective cloud management strategy does make processes like cloud email archiving and data compliance easier to manage, it is not just about how we handle data. It creates a roadmap that helps us maximize the data’s potential.
A good management strategy based on the four pillars mentioned earlier will create a strong data-driven organization that generates meaningful insights, ultimately providing better decision-making across the board.
James is the head of marketing at Tamoco
