The energy sector is a treasure trove of data – from seismic, drilling, and production records, to a host of other valuable information. However, with the amount of data generated and collected increasing every day, storing it all can be a costly affair. This is where efficient data management comes in – it enables energy companies to streamline their data storage, analysis, and utilization, making critical decisions, optimizing production, forecasting, and reducing operational costs. Proper data management practices can help energy companies achieve increased operational efficiency, reduced costs, and improved decision-making. In fact, effective data management is an essential ingredient for the success and sustainability of energy companies.
Cloud tiering is a data management technique that is widely used in the energy sector to optimize data storage and reduce storage costs. The energy sector generates and collects vast amounts of data, such as seismic, drilling, and production data, which needs to be efficiently managed, stored, and analyzed. With cloud tiering, energy companies can automatically move their data between different tiers of storage, based on the data’s level of importance, access frequency, and other defined criteria. For example, frequently accessed data can be stored in high-performance storage media like solid-state drives or magnetic disks, while less frequently accessed data can be moved to lower-cost, high-capacity storage media like cloud storage or tape-based storage.
Cloud tiering is often implemented using software-defined storage (SDS) solutions, which automate the process of data placement and movement across different storage tiers. This helps energy companies streamline their data storage, analysis, and use, ultimately contributing to increased operational efficiency, reduced costs, and improved decision-making. Advanced cloud tiering solutions take it a step further and use machine learning algorithms and metadata analytics to analyze data access patterns and move data to the most suitable storage tier based on its usage frequency.
The Challenges of Data Storage in the Energy Sector
As mentioned above, The energy sector generates and collects vast amounts of data from various sources. For instance, on average, 80,000 sensors on a modern offshore drilling platform generate data amounting to 10 TB/day. When you multiply it by the number of sensors across multiple geographies and days, the total becomes enormous. This data is used for various purposes, including optimizing production, improving safety, and reducing environmental impact. However, this data of little value unless it is analyzed, optimized, and mobilized. It becomes a sprawl that eventually turns into a swamp, leading to increased costs and reduced efficiency. Here are some common challenges faced:
- The ever increasing sprawl of unstructured data: 90% of data generated is unstructured. Sprawls of unanalyzed unstructured data lead to inefficient data usage and security and governance issues. Data storage becomes a pointless activity that results in increased storage costs and carbon footprint due to large-scale infrastructures. Moreover, 80% of the time, employees spend searching through unstructured data to make decisions and complete tasks. Four out of every five working days in the industry are devoted to researching unstructured data. If the data is not managed correctly, it won’t be accessible at the right time, resulting in delays in business processes, increased costs, and inefficient operations.
- The cost of storing and managing large amounts of data: Managing and storing large amounts of data can be a costly endeavor for energy companies. Traditional on-premise storage solutions require significant capital investments and ongoing maintenance costs, which can quickly add up. The average cost of storing a single terabyte of file data is estimated to be around $3,351 per year. However, this cost is just the beginning, as organizations must store data for extended periods to comply with regulatory requirements, and also account for IT resources like hardware, software, and personnel required to manage and safeguard their data. To make matters worse, up to 80% of this data is unstructured, meaning that organizations have no idea what’s in there but must still bear the cost of storing it, which can amount to millions of dollars. This situation doesn’t make sense from a financial perspective, as it’s simply a waste of money, time, and resources. The challenge lies in finding effective ways to manage unstructured data and ensure that only valuable data is stored, while the rest is discarded or archived.
- The need for secure & compliant data storage and management practices: Data breach costs in the energy industry ranked fifth behind the healthcare, financial, pharmaceutical, and technology industries. The cost of a breach in the energy industry is $4.65m, which is significantly more than average. The nature of the data collected and stored in the energy sector makes it attractive to cybercriminals seeking to steal valuable data or disrupt operations. Additionally, regulatory compliance requirements in the energy sector require companies to implement secure data storage and management practices to protect sensitive information and avoid costly fines. Data truly is the most important asset and the risk of mishandling or rogue data access can lead to massive reputational and financial impacts.
How can Cloud Tiering help?
Cloud tiering is a data storage technique that leverages cloud storage infrastructure to optimize data storage and management. It can help address the challenges associated with managing unstructured data by analyzing data access patterns and automatically moving data to the most appropriate storage tier. In cloud tiering, data is stored in multiple storage tiers based on the frequency of access, where frequently accessed data is stored in high-performance storage tiers, and infrequently accessed data is stored in lower-cost, slower storage tiers. Here’s how cloud tiering works:
- Data categorization: Cloud tiering begins with categorizing data based on its frequency of access. Frequently accessed data is stored in high-performance storage tiers, such as solid-state drives (SSD), while less frequently accessed data is stored in lower-cost, slower storage tiers, such as hard disk drives (HDD) or cloud-based object storage.
- Data movement: Once the data is categorized, the cloud tiering software automatically moves data between storage tiers based on its frequency of access. The most frequently accessed data is stored in high-performance storage tiers to ensure fast access times, while less frequently accessed data is automatically moved to lower-cost, slower storage tiers.
- Automated data retrieval: When data previously stored in a lower-cost, slower storage tier is accessed, the cloud tiering software automatically retrieves the data and moves it to a higher-performance storage tier for faster access.
- Data access and management: Cloud tiering provides a centralized platform for accessing and managing data across all storage tiers. This allows administrators to easily manage data from a single location, including backups, archives, and data retention policies.
- Scalability: Cloud tiering allows for scalable storage solutions that can be easily adjusted to meet changing data storage needs. Storage capacity can be added or removed without significant capital investments or infrastructure changes.
- Security: Cloud storage providers offer robust security measures, including data encryption, access controls, and multi-factor authentication, to ensure the security of stored data. Cloud tiering can help energy companies reduce the risk of data breaches and protect sensitive information by securely storing data in the cloud.
Cloud providers offer several storage tiers, each with its own price and performance characteristics. The tiers are categorized based on their access time, durability, and frequency of access. The most commonly used tiers are:
- Hot Tier: This tier is designed for data that is frequently accessed and requires low latency. It offers the highest performance and the lowest access time but comes at a higher cost.
- Cool Tier: This tier is for data that is accessed less frequently and requires a lower level of performance. It offers a lower cost than the hot tier but with higher access time.
- Archive Tier: This tier is for data that is rarely accessed, but still needs to be stored for compliance or legal reasons. The archive tier has the lowest cost but with the highest access time.
Use Cases of Cloud Tiering in the Energy Industry
Several energy companies have successfully implemented cloud tiering to optimize data storage and management. Here are some examples:
- ENGIE: ENGIE, a multinational energy company, implemented cloud tiering to manage data more efficiently and reduce storage costs. By leveraging cloud storage solutions, ENGIE could store inactive data in lower-cost storage tiers, while frequently accessed data was stored in higher-performance storage tiers. This approach helped ENGIE reduce storage costs and optimize its data management practices.
- Shell: Shell, a global oil and gas company, implemented cloud tiering to manage the vast amounts of data generated by its operations. By leveraging cloud storage solutions, Shell was able to store its data more efficiently and reduce storage costs. This approach also enabled Shell to improve its data management practices by providing centralized tools and services for managing its data.
- EDF Energy: EDF Energy, a leading energy supplier in the UK, implemented cloud tiering to manage its data more effectively and reduce storage costs. By leveraging cloud storage solutions, EDF Energy could store infrequently accessed data in lower-cost storage tiers, while frequently accessed data was stored in higher-performance storage tiers. This approach helped EDF Energy reduce storage costs and improve its data management practices.
- E.ON: E.ON, a European electric utility company, implemented cloud tiering to optimize its data storage and management practices. By leveraging cloud storage solutions, E.ON was able to store its data more efficiently and reduce storage costs. This approach also enabled E.ON to improve its data management practices by providing centralized tools and services for managing its data.
Implementing Cloud Tiering in the Energy Sector: Recommended Data Management Best Practices
- Identify the data that can be tiered: The first step is to identify which data can be moved to lower-cost storage tiers. Metadata analysis lays the foundation for enterprises to understand the data itself. Characteristics such as file ownership, processes/departments that are the largest consumer of data, when files were created, when files were last accessed, and what type and size files are just some of the data points captured and provided for reporting and decision making. Check out Data Dynamics’ Analytics suite for more information.
- Define a data retention policy: It’s important to define a retention policy for each type of data. This policy should outline how long the data needs to be retained, and the frequency of access. This will help determine the storage tier that each type of data should be moved to.
- Choose the right cloud storage provider: There are many cloud storage providers available, and it’s important to choose one that meets the needs of the energy sector. Factors to consider include security, compliance, and performance. Microsoft is one such provider that provides enterprises with best in class cloud tiering capabilities. Read more below.
- Consider hybrid cloud storage: A hybrid cloud storage solution can provide the best of both worlds. This approach allows organizations to keep frequently accessed data on-premises, while moving infrequently accessed data to the cloud.
- Implement automation: Cloud tiering can be a complex process, especially for large amounts of data. Implementing automation can help ensure that data is moved to the appropriate storage tier in a timely and efficient manner. Policy-based file data migration from heterogeneous storage into the private and public cloud and on-premises storage ensures minimal to no risk with automatic access control and file security management. Check out Data Dynamics’ Mobility suite for more information.
- Monitor and manage data: It’s important to monitor and manage data regularly to ensure that it is being stored in the appropriate storage tier. This includes monitoring access patterns and adjusting retention policies as needed. The optimum solution is to use a unified data management software that gives you a single-pane view of enterprise data and drives cloud data management. Check out Data Dynamics’ Data Management Platform for more information.
- Ensure data security: Cloud tiering can introduce new security risks, such as data breaches and data loss. It’s important to implement appropriate security measures, such as encryption and access controls, to protect data at all times. It is important to conduct pre and post-data migration data analysis. One can gain insight into the data through content and context analysis during and after migration to secure and remediate the PII/sensitive data to meet compliance requirements. Check out Data Dynamics’ Security suite for more information.
Implementing cloud tiering in the energy sector requires careful consideration of data types, storage tiers, cloud storage providers, security, and compliance. By following best practices and considering these factors, energy companies can successfully implement cloud tiering to optimize their data storage and management practices, reduce storage costs, and enhance data security and compliance.
Microsoft Azure: Your Partner of Choice
Microsoft Corporation is one of the largest technology companies in the world. The company is best known for its software products, including the Windows operating system and Microsoft Office suite. In recent years, Microsoft has also become a major player in the cloud computing industry with its Azure cloud platform.
Cloud tiering is a feature of Azure that allows users to manage the storage of their data across different tiers based on usage patterns and access frequency. The idea behind cloud tiering is to help users optimize their storage costs by automatically moving less frequently accessed data to lower-cost storage tiers, while keeping frequently accessed data in high-performance tiers.
Microsoft Azure provides several options for tiering data in the cloud, including Azure Blob Storage and Azure File Sync.
Azure Blob Storage is a highly scalable and cost-effective storage solution for unstructured data, such as images, videos, and documents. Blob Storage supports three access tiers: hot, cool, and archive. Hot tier is optimized for frequently accessed data, while cool tier is optimized for data that is accessed less frequently, but still needs to be readily available. Archive tier is optimized for data that is rarely accessed, and can be stored at a lower cost.
Azure File Sync is a hybrid cloud storage solution that enables organizations to store less frequently accessed data on-premises, while keeping frequently accessed data in Azure. With Azure File Sync, organizations can choose to tier data based on access frequency, age, or other attributes.
Azure also provides tools for automating the tiering process, such as Azure Blob Storage lifecycle management and Azure File Sync cloud tiering. These tools allow organizations to set retention policies, automate data movement, and optimize storage costs.
The Azure cloud tiering feature allows users to create policies that automatically move data between different tiers based on usage patterns. For example, a user might create a policy that moves data that hasn’t been accessed in 30 days from the hot tier to the cool tier. Another policy might move data that hasn’t been accessed in six months from the cool tier to the archive tier. These policies help users optimize their storage costs by moving less frequently accessed data to lower-cost tiers.
In addition to tiering, Azure provides several other data management features, such as encryption, access controls, and data backups. These features can help organizations in the energy sector to secure their data, comply with regulations, and protect against data loss.
Microsoft’s cloud tiering feature in Azure is helping users optimize their storage costs by automatically moving less frequently accessed data to lower-cost tiers, while keeping frequently accessed data in high-performance tiers. The feature provides users with granular control over their storage costs and performance, helping them to make informed decisions about their storage needs.
The Data Dynamics Advantage
Transforming data management in the energy industry has many benefits, including reduced carbon footprint and improved operational efficiency & performance. For digitalization and automation, the energy industry is heavily reliant on data. Data Dynamics’ Unified Unstructured Data Management Platform is crucial in improving conventional, unconventional, and midstream operations in the energy industry. By incorporating our unified data management platform, energy companies can efficiently manage, process, and secure immense datasets from upstream, midstream, and downstream operations.
Data Dynamics’ metadata analytics also assists enterprises by providing insights into the structure and organization of data, which can be useful in determining the value and strategic significance of specific data assets during cloud tiering. This information can help to identify which data assets are critical to the business and should be retained, archived, or eliminated. Additionally, Data Dynamics provides information on the dependencies and interrelationships between data assets, which can inform decisions on how to separate and transfer data assets between organizations or storages. Overall, by facilitating data alignment and refinement, we enable our customers to transform data from existing in a stored state into a business asset and achieve cost optimization through intelligent cloud tiering.
The Data Dynamics’ Unified Data Management Platform features a modular setup with four independent yet interconnected modules (Analytics, Compliance, Security and Mobility) that help to eliminate data sprawl and its associated security challenges. The platform uses artificial intelligence and machine learning technologies to help enterprises gain critical and accurate insights into unstructured file metadata for storage optimization and content analytics for PII/PHI/sensitive data discovery, storage visibility, and infrastructure optimization. By facilitating data alignment and refinement, we enable our customers to transform data from existing in a stored state into a business asset. Proven in over 300+ organizations, including 28 Fortune 100 and 2 of the five largest energy enterprises, the Platform is a one-stop solution that enables energy organizations to fully capitalize on the capabilities of unstructured and high-volume data and realize competitive advantages.
As a part of our ‘accelerating cloud adoption’ objective, we have recently partnered with Microsoft Azure to help enterprises migrate data into Azure at zero cost. Now organizations can move their unstructured files and object storage data into Azure without paying a cent or purchasing separate migration licenses. Migrations are automated, ensure minimal risk with automatic access control and file security management and deploy intelligent data management across On-Premise, Azure, and Hybrid Cloud.
Click here to check out how Data Dynamics helped one of the world’s seven multinational energy “supermajors“ Fortune 50 Company migrate 600 TBs of data in 20 days and cost savings of millions of dollars in data center closure.