Top Five Benefits of AWS GRC Solutions

Implementing AWS’s GRC solutions offers several advantages that go beyond compliance. Here are the top benefits: • Data-Driven Decision Making: Real-time monitoring and analytics enable organizations to make informed decisions that align with both strategic goals and compliance objectives. • Fostering Responsible Operations: By promoting a culture of governance and ethical practices, AWS helps organizations operate responsibly and build trust. • Advanced Security Measures: Features like encryption, identity management, and continuous threat detection provide robust protection for sensitive data. • Scalability and Flexibility: AWS solutions scale with your business, ensuring that governance and compliance measures grow alongside your operations. • Cost-Effective Operations: AWS’s pay-as-you-go model allows organizations to optimize their IT budgets while maintaining governance and compliance standards.

AWS and GRC Tools

Amazon Web Services (AWS) provides a comprehensive set of GRC tools and practices that can be integrated into the Governance, Risk Management, and Compliance (GRC) framework that empower businesses to effectively manage their data while adhering to industry standards and regulations. Below are some examples of AWS and GRC (Governance, Risk, and Compliance) tools and practices:

Governance: Establishing a Solid Framework

In the AWS ecosystem, governance refers to setting up policies, guidelines, and processes to ensure effective data and resource management. This framework supports business objectives while promoting ethical practices, transparency, and adherence to regulatory requirements. AWS provides several GRC tools and practices that centralize governance and enhance control over accounts, resources, and configurations. • AWS Organizations: This tool helps organizations manage multiple AWS accounts in one place, allowing for the easy implementation and enforcement of policies across the enterprise. Through Service Control Policies (SCPs), organizations can control permissions and ensure only authorized actions occur. • AWS Config: AWS Config is essential for governance as it tracks changes in AWS resource configurations. By providing detailed insights into the state and relationships of these resources over time, AWS Config ensures compliance with internal and external standards. • AWS Service Catalog: The AWS Service Catalog allows organizations to maintain oversight of their IT environment by managing catalogs of approved services. This guarantees that only pre-approved and compliant software, databases, and configurations are deployed. • AWS Control Tower: AWS Control Tower simplifies setting up and managing a secure, multi-account AWS environment. It automates governance best practices and continuously monitors compliance with pre-configured guardrails.

Risk Management: Safeguarding Against Threats

Identifying and managing risks is crucial in today's digital landscape. AWS offers a range of services to help organizations monitor their infrastructure, detect potential vulnerabilities, and respond to security threats swiftly. • AWS CloudTrail: CloudTrail logs and monitors API activity within AWS, allowing organizations to trace user actions and conduct investigations after security incidents. It’s also useful for forensic analysis to determine the cause of issues. • AWS Security Hub: As a centralized security dashboard, AWS Security Hub aggregates findings from multiple AWS services, helping businesses streamline incident response and maintain compliance. • Amazon GuardDuty: GuardDuty is a security service that detects suspicious activities and unauthorized behavior in AWS accounts. By leveraging machine learning and threat intelligence, it helps organizations preemptively address potential risks. • AWS Config Rules: These customizable rules automatically check resource configurations for compliance. If a resource deviates from the expected settings, alerts are triggered, enabling proactive issue resolution.

Compliance: Ensuring Adherence to Regulations

Compliance is vital for any organization handling sensitive data. AWS simplifies the process with a variety of tools to help organizations meet regulatory requirements and reduce audit burdens. • AWS Artifact: AWS Artifact offers on-demand access to important compliance documents, such as SOC reports and certifications like ISO and PCI DSS. This is especially helpful during audits, providing immediate access to evidence of AWS's adherence to standards. • AWS Shield & AWS Web Application Firewall (WAF): These services protect against DDoS attacks and unauthorized access attempts, ensuring web application availability and data integrity. Shield and WAF work together to filter out malicious traffic and ensure the security of incoming requests. • AWS Key Management Service (KMS) & AWS Certificate Manager (ACM): Data encryption is critical for compliance, and AWS KMS helps manage encryption keys securely. ACM automates the deployment of SSL/TLS certificates, protecting data both in transit and at rest. • AWS Audit Manager: AWS Audit Manager automates evidence collection for audits, continuously assessing your environment against industry standards. This reduces manual effort and ensures that organizations remain consistently compliant. AWS’s robust GRC framework empowers organizations to effectively manage data, mitigate risks, and ensure regulatory compliance. Leveraging AWS’s advanced tools not only supports meeting industry standards but also fosters innovation, resilience, and future-readiness within businesses.

Beinex: AWS Partner for the Middle East

Beinex is an AWS consulting partner, and we empower customers with AWS managed services to host their BI solutions and much more on the cloud. Our cloud migration experts bring in best-in-class stability and reliability by understanding your business strategy and working closely with you to deploy AWS infrastructure as a service. Connect with Us for a Free Demo Interested in our services? Try AWS for free: https://beinex.com/beinex-amazon-web-services/

What could be the Cloud computing trends to look forward to in 2023? Let’s have a look

1. Utilising Edge Computing
2. AI and ML Services
3. Disaster Recovery
4. Multi and Hybrid Cloud Solution
5. Cloud Security and Resilience
6. Cloud Gaming
7. Kubernetes and Docker
8. Serverless Computing
9. Blockchain
10. Metaverse
11. IoT

Let’s deep-dive:

1. Utilising Edge Computing

In the world of cloud computing, edge computing is one of the most popular trends. Here, data is evaluated geographically nearer to its source and stored and processed at the network's edge. As modern internet technologies emerged, the internet speed has helped in reducing latency, technologies such as 5G is used more frequently, and processing can be done swiftly. Greater privacy, quicker data transmission, security, and improved efficiency are just a few of the primary advantages of edge computing. Edge computing is expected to be at the core of every cloud strategy in 2023, making it the most important development in this area.

2. AI and ML Services

Two technologies that are closely related to cloud computing are artificial intelligence and machine learning. Due to the volume of data processed for the machine to learn patterns, this area demands faster processing and abundant storage requirements for training algorithms and data collection respectively. Due to the availability of virtually infinite computational capability, on-cloud AI and ML services are more cost-effective on the cloud. Cloud computing is used for handling enormous amounts of data to raise productivity at tech firms. Increased self-learning and automation capabilities, improved data security, and more individualised cloud experiences are the main trends that are most likely to arise in this fiel

3. Disaster Recovery

The ability to have a DR site in a geographically remote area helps to quickly restore vital services in the event of a natural or man-made disaster. It describes the process of employing cloud-based resources to recover from a disaster in the event such as power outages, data loss, or device failure/problems.

4. Multi and Hybrid Cloud Solution

Many businesses have embraced a multi-cloud and hybrid IT approach that mixes legacy platforms, on-premises, dedicated private clouds, and several public clouds. They provide a mix of public and private clouds tailored to the requirements of particular firms where several business drivers matter for instance like those of insurance, banks, etc. Multi-cloud and hybrid cloud solutions will thus be among the most popular cloud computing trends in 2023 and the years to come.

5. Cloud Security and Resilience

When companies shift to the cloud, there are still several security vulnerabilities. Investment in cyber security and building resilience against everything from data theft to the consequences of a pandemic to global trade will become more crucial and major variables in the coming years. The use of managed "security-as-a-service" providers, AI, and predictive technologies will increase in 2023 as a result of this trend to identify risks before they result in problems. Studies say that leading vendors of cloud computing invest over a billion dollars every year to protect their customers’ data.

6. Cloud Gaming

Cloud gaming platforms operate similarly to remote desktops and video-on-demand services; games are stored and executed remotely on a provider's dedicated hardware and streamed as video to a player's device via client software. It can be advantageous as it eliminates the need to purchase expensive computer hardware or install games directly onto a local game system. Cloud gaming can be made available on a wide range of computing devices, including mobile devices such as smartphones and tablets, digital media players, or proprietary thin client-like devices. Microsoft, Sony, Nvidia, and Amazon all offer video game services. But video game streaming requires more data and is only doable with fast internet. With the launch of 5G in 2023, the cloud gaming sector will grow significantly.

7. Kubernetes and Docker

The main trend is the growing use of container orchestration tools like Kubernetes and Docker. Large-scale deployments that are extremely scalable and effective are made possible by this technology. These are expandable, open-source platforms that manage services and workloads from a central location while running applications from a single source. Both platforms offer high scalability and efficiency. Over the following several years, Kubernetes and Docker will continue to play a significant role in cloud computing trends as they are developing quickly.

8. Serverless Computing

Because of the advent of the sharing economy, serverless computing entered the computing sector. Instead of being deployed on physical servers in this case, compute resources are offered as a service. This indicates that instead of needing to maintain its servers, the company only pays for the resources it uses. Additionally, serverless cloud solutions are growing in popularity because of how simple they are to use and how rapidly one can design, deploy, and expand a cloud solution. Overall, this technology is a trend that is just starting and is becoming more and more popular.

9. Blockchain

Blockchain, which users continue to follow more and more, is a connected list of blocks containing records. Blocks of data are stored using cryptography. It has outstanding decentralisation, security, and transparency. In conjunction with the cloud, it is currently utilised more frequently. It can securely and affordably process enormous volumes of data and regulate documents. For many industrial applications, the new technology is beginning to hold out a great deal of promise.

10. Metaverse

The days are not long for the Metaverse and cloud computing to become inextricably linked to each other. The metaverse will compel businesses to migrate to cloud infrastructures to host their virtual worlds. Massive amounts of workloads will be migrated, paving the path for even more innovations to model their virtual worlds. Considering the difficulties of building a metaverse without highly available and scalable premises and hosting grounds, the adoption of cloud computing will be inevitable. As more layers of complexity will be added to the metaverse as it matures, the need for a strong foundation to support the whole thing and to deliver a flawless user experience with no backend issues will arise. Consequently, cloud providers engaged in the metaverse will create metaverse-compatible solutions to assist businesses in quickly establishing their virtual space.

11. IoT

In the realm of cloud computing, IoT is a well-known trend. Connectivity between computers, servers, and networks is maintained by this technology. It performs the role of a middleman, guarantees effective communication, and helps gather data from distant devices. Due to the enormous data produced by IoT devices, it requires many terabytes of storage. Since the cloud, the storage of data has become cheaper. In recent years storing and processing machine-generated data has become relatively easier. In the coming years, businesses would be able to efficiently analyse data from IoT devices and make informed decisions.

Summing Up

Even though cloud computing has been present for more than a decade, its popularity has skyrocketed in recent years. Given this growth trajectory, cloud computing is on track to become the most discussed technology in 2023. Recent studies show that by 2028, the cloud computing market is anticipated to be worth more than $1 trillion. Being the game changer, its impact will grow along with the adoption in the coming years too.

Beinex Offerings

Beinex is all about transforming the way organizations work with data to bring out the best in Business, Technology and People. Our association with Snowflake, a leading cloud-first data warehouse service, is a partnership that we leverage to support the data analytics solutions that we offer our clients.

Snowflake Data Sharing

Data sharing in Snowflake equips you to share specific objects with another Snowflake account or a designated reader account. The beauty of this process lies in the fact that the data isn't duplicated or moved between accounts.
Now, why is this a game-changer for organisations? When constructing data pipelines and developing data products, it's a common practice to shuttle data between databases and diverse systems to blend different datasets.
Consider this scenario: You have transactional data within your online transactional processing (OLTP) database, and you wish to integrate it with external data for a machine learning model. Traditionally, organizations would export data into a data lake, import external data, and then employ tools like Apache Spark for analysis.
But what if, instead, you could simply deposit your data into Snowflake, and the external data source could seamlessly share its data with your organisation, eliminating the need to load it separately? This eradicates the challenge of keeping data copies synchronised, resulting in savings on storage, computing costs, and maintenance efforts.
Imagine your company possesses valuable information that can guide other companies in making informed decisions. For instance, let's say your company can provide precise estimates for product delivery times based on proprietary data, and you want to offer this information for sale to your customers.
Enter Snowflake data sharing—it empowers you to precisely do that.

Case Studies: Snowflake Data Sharing

Citing two instances where leading organisations use Snowflake to improve actionable data sharing, collaboration and reporting capabilities.

1. A Pioneering Technology Leader A well-known Swedish-Swiss multinational corporation successfully implemented a streamlined data strategy using the Snowflake Data Cloud, adopting an "extract once, use everywhere" approach that simplified data consolidation and enablement. By transitioning from nightly extracts, which caused significant system overhead, to a single, near real-time Change Data Capture (CDC) process, the company achieved efficient replication of information to Snowflake with minimal impact. The utilisation of Snowflake Secure Data Sharing facilitated secure and governed data collaboration across the four business areas.
2. A Leading fast-food Restaurant Chain Snowflake's data-sharing capabilities have revolutionised decision-making for a fast-food restaurant chain. They can effortlessly share crucial sales, inventory, and operational data with external entities, expanding from three to over 30 parties.
With a high-performance database platform hosting over 2 million transaction records, the restaurant chain has established a robust data management and analysis infrastructure through Snowflake, empowering its operational and marketing endeavours.
Moreover, by consolidating all data onto Snowflake, the organisation has achieved a remarkable 70% reduction in operational IT costs, demonstrating the platform's efficiency and cost-effectiveness.
Centralising and sharing data with Snowflake significantly eased the development of data products for various purposes, including marketing campaign analytics, quotation success metrics, production line tools, and supply chain dashboards. These data products are utilised by thousands of users globally, including internal stakeholders and external vendors, enhancing collaboration and efficiency across the organisation.

What are the best practices for Snowflake data sharing?

Optimize your Snowflake data sharing experience with these essential practices. Ensure data security by utilizing secure views to filter and mask sensitive information. Enhance clarity and understanding by employing descriptive names and comments for your shares. Monitor and fine-tune your sharing activities using Snowflake Information Schema or Account Usage views. Foster communication and collaboration with your consumers to create a seamless workflow.
Take command of your data sharing environment by setting quotas and limits with the ALTER SHARE command. Keep your consumers informed about any changes or updates to your shares, and actively seek feedback to refine your data-sharing strategy. Explore additional data sources through Snowflake Data Exchange or Data Marketplace to enrich your analytics.
These best practices safeguard sensitive data, ensure compliance with data privacy regulations, clarify the purpose of each share, and provide insights into usage and performance, ultimately enhancing your data analysis capabilities. Below are some best practices for data sharing with Snowflake:

1. Understand Snowflake Data Sharing
Familiarize yourself with Snowflake's data sharing features, such as Secure Data Sharing (SDS) and Sharehouse, to leverage the platform effectively.

2. Role-Based Access Control (RBAC)
Implement strong RBAC policies to control who can share data and who can access shared data. Define roles and permissions to ensure data security and compliance.

3. Secure Data Sharing
Use Secure Data Sharing (SDS) to securely share data with external parties without copying or moving the data. Implement encryption and access controls to protect sensitive information.

4. Sharehouse Best Practices
If using Sharehouse, follow best practices for creating and managing share objects. This includes defining share schemas, tables, and using the appropriate share options for your use case.

5. Data Masking and Redaction
Apply data masking or redaction policies to shared data to protect sensitive information. Ensure that shared data complies with privacy regulations and internal data governance policies.

6. Query Performance Optimization
Optimize query performance for shared data by using clustering keys, partitioning, and indexing. This helps enhance the efficiency of queries on large datasets.

7. Versioning and Change Tracking
Implement versioning and change tracking mechanisms to keep track of updates and changes in shared data. This ensures data lineage and helps with auditing and troubleshooting.

8. Documentation and Metadata
Maintain comprehensive documentation and metadata for shared datasets. Include information about the source, purpose, and any transformations applied. This helps users understand the shared data context.

9. Governance and Monitoring
Establish governance practices for data sharing, including regular reviews of shared data objects and access logs. Monitor data-sharing activities to identify any anomalies or potential security issues.

10. Educate Users
Provide training and documentation for users involved in data-sharing activities. Ensure they understand the best practices, security protocols, and the impact of data sharing on performance.

11. Regular Audits and Reviews
Conduct regular audits and reviews of shared data objects, permissions, and access controls. This helps maintain data integrity, security, and compliance with organizational policies.

12. Cost Monitoring

Keep an eye on the costs associated with data sharing, especially if you're sharing data externally. Understand the pricing model and optimize data sharing configurations to manage costs effectively.

By adhering to these best practices, you can:
1. Shield Sensitive Data: Employ secure views to fortify sensitive information.
2. Navigate Data Privacy Regulations: Ensure compliance with data privacy regulations by controlling access and usage.
3. Illuminate the Purpose of Each Share: Maintain transparency regarding the intended purpose and content of each shared dataset.
4. Efficiently Monitor Usage and Performance: Keep a finger on the pulse of usage patterns and optimize performance for streamlined data sharing.
5. Elevate Your Data Analysis Journey: Enrich your analytics by exploring diverse data sources and unlocking fresh perspectives.

What’s Next

1. Enhanced Data Collaboration Tools:

Snowflake is expected to introduce advanced features for more streamlined and efficient data collaboration, addressing the evolving needs of industries.

2. Innovations for Privacy-Preserving Analytics:

Snowflake aims to develop and implement solutions that uphold data privacy while enabling powerful analytics, aligning with the growing concerns in this area.

3. Adaptation to Changing Industry Dynamics:

Snowflake is likely to evolve its platform to meet the challenges posed by changes in industry dynamics, ensuring it remains a robust solution for data management and collaboration.

4. Integration of Cutting-Edge Technologies:

Snowflake may integrate emerging technologies, enhancing its capabilities to support new use cases and data-intensive analytic methods.

5. Continued Emphasis on Secure Data Collaboration:

Future updates from Snowflake may include even more robust security measures and innovations in data clean rooms, reflecting a commitment to secure data collaboration in the face of a dynamic data landscape.

Best Way to Share Data for Your Business

For secure collaboration, old ways of copying data are no longer the best. If you're working with trusted partners and it's privacy-compliant, Snowflake Secure Data Sharing is a quick and secure option. But, if you're dealing with sensitive or regulated data, especially when the risk is high, consider using a data clean room for an extra layer of security and compliance.

Beinex + Snowflake Offerings

Beinex’s partnership with Snowflake enables us to offer you advanced features like automated tuning and elastic compute, along with analytics modernisation services, to help your organisation realise exponential Return on Investment.

AWS: Four Types of Cloud Business Value

In the era of digital transformation and infrastructure modernization, the journey to the cloud has been both exhilarating and challenging. Many businesses have successfully migrated their "easy" applications to the cloud. However, a prevailing concern lingers among business leaders—an uncertainty about the returns on investment in terms of time and effort. Questions arise about productivity gains, data security, and the impact on critical agility metrics, such as time to market. Here, we delve into the distinct results observed by AWS users across four pivotal domains of cloud business worth: cost efficiency, workforce efficiency, resilience, and adaptability.

1. Cost Savings: More Than Meets the Eye

Migrating infrastructure to Amazon Web Services (AWS) yields significant cost savings, averaging around 20% in total infrastructure expenses. Top performers witness a staggering 47% reduction, highlighting the potential for substantial savings. Yet, the nuances lie in application-specific cost reductions that vary based on factors like application complexity and cloud tenure.

Studies reveal a significant financial shift for organizations venturing into AWS migration. On average, businesses witness a remarkable 20% reduction in total infrastructure costs—a noteworthy achievement translating to a staggering $69 million slashed from an average pre-migration annual IT spend of $345 million. However, the journey to AWS doesn’t merely stop at these impressive numbers. For top performers, the stakes are higher, yielding an exceptional 47% savings in total infrastructure costs. This equates to a colossal $164 million reduction from an average annual IT spend of $349 million. (Refer to Fig. 1 for a graphical representation.) Fig.1 Study participants also provided data for up to three specific applications transferred to AWS, allowing the calculation of cost savings specific to these applications. On average, infrastructure costs related to these applications witnessed a consistent decline of around 20% annually over a span of six years post-deployment. Following migration, the extent of cost reductions varies among different application types. Multiple factors influence this variability, including the complexity of applications, their level of modernization and optimization before and after migration, and their duration within the cloud. Notably, patience yields rewards in this scenario. Analysis of application costs based on their tenure in AWS demonstrates an incremental improvement in savings rates with each passing year. (Refer to Fig. 2 for a graphical representation.) Fig.2 Comparative analysis between cloud and on-premises deployments highlights a positive correlation between increased cloud adoption and various efficiency metrics.

Nearly 3X lower total cost for procurement functions compared to equivalent on-premises solutions.

A $0.24 decrease in HR costs for every dollar invested in cloud.

Labor cost reductions of 18% to 20% in both HR and finance.

A 4% increase in HR productivity (output) for every dollar invested in cloud.

A productivity increase of 7% to 12% in procurement.

Factors impacting potential cloud cost savings include baseline infrastructure costs, application types, duration in the cloud, and post-migration innovations. Organizations with high infrastructure spending can see a 41% reduction after migration compared to the 20% average. Additionally, AWS migration leads to a 23% cut in overprovisioned application capacity, optimizing efficiency and reducing unnecessary costs.

2. Workforce Efficiency

Following the migration of applications to AWS, there's a noticeable enhancement in IT infrastructure staff productivity among respondents. They report a remarkable 66% rise in the number of retained VMs managed per administrator. Such post-migration efficiencies enable a strategic shift, allowing 17% of staff positions to transition from routine infrastructure maintenance to pivotal roles focusing on infrastructure planning, architecture, orchestration, and innovation (Refer to Fig. 3 for visual representation)

Fig.3 Moreover, a substantial productivity boost unfolds within development teams post-AWS migration. There's a notable 29% increase in developer time dedicated to crafting new features and functionalities, shifting from minor updates handled by cloud providers. Leveraging AWS developer tools streamlines coding processes, further amplifying developer productivity. These enhancements result in a 32% average reduction in the time interval between production releases for migrated applications. This surge in productivity not only streamlines operations but also empowers organizations to overcome the barrier to innovation identified by respondents—the challenge of dedicating ample time to innovation amidst other pressing concerns.
A commercial finance organization exemplifies the tangible impact of AWS migration on innovation. Their technology division experienced a significant leap in developer focus post-migration. Initially allocating 20% of developer time to crafting new features, their shift to AWS elevated these efforts drastically. For customer relationship management and business intelligence, the focus surged to an impressive 60%, witnessing a threefold increase. However, the transformation was even more substantial for their migrated financial planning and analysis system, skyrocketing from a mere 20% pre-migration to a staggering 80% post-migration—showcasing an unparalleled fourfold increase.

3. Resilience

Cloud technology has redefined resilience by elevating system availability, reducing latency, and fortifying security measures. The disruptive impact of the pandemic accentuated the criticality of resilience, surpassing the effectiveness of traditional disaster recovery approaches and redundant data centers. Cloud-based infrastructure emerged as a crucial linchpin, ensuring uninterrupted operations during tumultuous times.
The scalability inherent in cloud services played a pivotal role during the pandemic, exceeding initial capacity plans by an astounding 90%. This scalability was instrumental in swiftly connecting and supporting remote workers, effectively mitigating disruptions. Chief Information Officers (CIOs) emphasized that their previous migration to AWS significantly facilitated the accommodation of sudden surges in demand, underscoring the importance of cloud infrastructure in maintaining seamless operations during critical periods.
A U.S.-based healthcare nonprofit's strategic migration of its last on-premises ERP system to the cloud in 2019 fortuitously positioned it for the subsequent shutdowns and challenges brought on by the pandemic. The seamless integration of cloud technology enabled the organization to navigate and maintain operational continuity amidst adversity, highlighting the indispensable role of cloud solutions in supporting mission-critical functions and adapting to hybrid office-remote work models.
In today's digital commerce landscape, system downtime carries profound consequences far beyond inconvenience. It significantly impacts businesses, directing customers towards competitors' platforms. The financial implications of downtime are staggering, averaging 79 minutes and costing approximately $84,650 per hour in 2020. Furthermore, the aftermath of data breaches and ransomware attacks extends beyond financial costs, causing public embarrassment and substantial recovery expenses, averaging $4.6 million for cyberattacks and $4.2 million for data breaches.
The migration to AWS represents a transformative milestone, significantly bolstering both availability and security. Many key resilience Key Performance Indicators (KPIs) exceeded the 50% mark, as illustrated in Fig. 4. This substantial enhancement underscores the transformative impact of AWS migration in fortifying operational resilience and proactively mitigating potential threats.

Fig.4

4. Adaptability

The most strategic of all cloud migration benefits, agility equips organizations for success in a digital business environment. Agility refers to the ability to respond quickly and effectively to changes in business conditions or disruptive business events. Broadly speaking, the more technology infrastructure an organization has in the cloud, the more agile it can be. A study by The Hackett Group on agility in business services functions (i.e., finance, HR, IT, and procurement), found that the most agile organizations have 41% of their infrastructure in the cloud, compared to just 29% for the average respondent.
Winning in a digitally competitive industry or market depends heavily on agility in product development. A major aspect is the speed at which new technology-enabled products and features are brought to market. For applications in the cloud, technology organizations are better able to use agile/DevOps methodologies thanks to services that simplify and accelerate provisioning infrastructure, deploying application code, automating software release processes, and monitoring application and infrastructure performance. These changes, combined with the development-team productivity gains discussed earlier, contribute to a 43% decrease in time to market and a faster pace for production releases (Fig. 5).

Fig.5

Recommendations

The Cloud Services Study underscores how migrating to AWS drives substantial business value across cost savings, staff productivity, resiliency, and agility. It dispels the notion that the cloud is solely a cost-saving venture, highlighting its strategic superiority over traditional on-premises infrastructure. The agility alone—enabling quicker time to market, enhanced insights, and frequent production releases—positions organizations competitively in the digital sphere. This transformative shift from infrastructure management to innovative development is a pivotal game-changer.
In forthcoming reports, we'll delve deeper into specific migration strategies and cloud financial management practices that contribute to superior outcomes. Meanwhile, here are key insights from this study:

Migration's financial benefits transcend infrastructure cost reductions. Anticipate increased efficiencies in application provisioning, reduced security incidents, minimized downtime, and amplified agility.

Optimize cloud costs post-migration. Implement strategies like consumption-based pricing and best practices in cloud financial management, leveraging tools like AWS Cost Explorer for uncovering cost-saving opportunities.

Cloud hosting should form a fundamental aspect of any digital transformation strategy. Prioritize migrating core applications and data to AWS to enable faster data access, insight generation, and expedited time to market, essential for competing in digitally advanced sectors.

Cloud serves as a crucial pillar for future workforce enablement. The accessibility and scalability of AWS-hosted data and applications support hybrid or digital workforces, characterized by constant mobility, adaptable headcounts, and seamless real-time access to highly secure systems.

The pandemic experience validated the efficacy of cloud-based infrastructure as a robust defense against catastrophic disruptions. Accelerated cloud migration should feature prominently in every business continuity investment strategy and resiliency improvement roadmap.

Most of the companies operating today are data-driven as they have started identifying the value of data. The value of data and data marketplaces are evolving with the growth of big data and data requirements of companies.

Data Marketplace

In simple terms, these are online marketplaces where we can buy and sell data of any sort. Data marketplaces offer several kinds of data from a wide range of different data sources. These data include Business Intelligence, demographics, research, and marketing data. Data types are structured and offered to clients by data providers. Providing buyers with more choice of high-quality data generates more engagement and encourages fair pricing between the sellers. Every company has the potential to earn revenue from the information it generates. In a recent study of more than 400 organizations, only 1 in 12 were monetizing their data to its fullest extent. Modern data monetization strategies can help you open brand new revenue streams. There are 3 key steps to monetize your data and drive new revenue streams.

Understand your Data Offerings - What types of data or data services are you producing that would be valuable to other organizations?

Decide How to Price Data Products - What should be the pricing strategy followed, and how easy would it be to put into action?

Know About Data Sharing Methods - Which distribution channel should be selected for data sharing that adheres to GDPR and data governance policies?

Once you have decided on the data offerings and priced the data products, the key to successfully monetize your data is by sharing the data with the clients/ prospects. The customers and business partners would be eager to get data from you, especially if you can make the process easy and secure. Traditional data sharing technologies often use FTP, Cloud Storage, or API. These methods generally do have few disadvantages.

1. Storage costs for both vendors and buyers
2. ETL costs and effort
3. Security vulnerabilities
4. Service and support costs
5. Latency and potential errors leading to poor customer experience

How do we overcome these challenges? There are platforms that make revenue generation easier with secure data sharing methodologies. Snowflake is one of the most secure and innovative platforms.

Snowflake & Data Monetization

Snowflake is an analytic data warehouse provided as Software-as-a-Service (SaaS). It provides a data warehouse that is faster, easier to use, and far more flexible than traditional data warehouse offerings. Snowflake allows companies to easily publish a variety of data sets that become immediately available for use or purchase for clients. Snowflake Data Exchange, a modern data sharing method, reduces the time to market and significantly influences customer success. Data Exchange is your own data hub for securely collaborating around data between a selected group of members that you invite. It enables providers to publish data that can then be discovered by consumers. The benefits of Snowflake Data Exchange over Traditional Data sharing Methods are:

1. Secure Data Sharing
   • Exchange data within your organization between different business units. Collaborate with external parties such as vendors, suppliers, partners, and customers.
2. Reduce Time to Market
   • Break down data silos and reduce time to market.
   • Interchange data with third-party vendors to help augment internal datasets.
   • Break down data silos by scaling multiple data sets from different sources within your organization.
   • Find and consume data on other Data Exchanges to get business insights.
3. Speed of Processing
   • Snowflake’s multi-cluster shared data architecture is designed to process enormous quantities of data with maximum speed and efficiency.
   • All data processing horsepower within Snowflake is performed by one or more clusters of computing resources.
   • Data is cached locally within computing resources, along with the caching of query results, to improve the performance of future queries.
4. Cost Benefits
   • The costs for sharing data with Snowflake are minimal and straightforward.
   • Simply pay for the data you store, i.e., you only pay for what you use.
   • Reduce extract, transform, load (ETL), and data pipeline maintenance costs.
5. Control and Govern Access
   • Managing membership
   • Granting and revoking access to data through standard and personalized listings
   • Auditing data usage
   • Applying security controls to your data

Snowflake promises to accelerate the data exchanges by reducing the barriers to access data and time to market. It increases the intrinsic value of data by allowing to share and access of data between providers and consumers.

Real-life Implementation

A famous telecom organization in Europe was sitting on large silos of data that they could not monetize properly because of the complex architecture of the data warehouse operations and data security challenges involved in the data sharing process. The company has Customer Daily Records (CDR) of its subscribers that contains location data of the users. This data can be used to identify the places people visit and help with building consumer profiles. The gathered data allows advertisers to target messages to specific users while tracking whether they visited a retail store after seeing a mobile ad. This helps them plan personalized marketing strategies and business goals based on demography profiles for targeted users. However, due to the data privacy policies of the European Union like GDPR, organizations were struggling to share data with their potential clients. The GDPR policy makes it mandatory for organizations to ensure that the customer's personal information is not shared with third parties without the customer's consent and involves hefty fines and penalties for the data breach. Even the data sharing process was a source of concern as the data was often shared in text/excel files because of the different database architecture of the clients. With growing data privacy concerns and challenges in creating datasets adhering to the GDPR policies, organizations are strictly asked not to share customer data with third parties. The current system architecture forced the organizations to employ a large number of resources to extract the data from the database system and ensure that customer data is not compromised at any point. The companies were evaluating the possibilities of a potential system that would help them monetize the data they currently hold. The introduction of Snowflake into the organizational architecture solved the data monetization problem and improved the overall data culture in the organization. The unique architecture of Snowflake separates the data storage and computation layer to enhance organizational productivity. The pay as you use policy of the Snowflake and the zero maintenance of infrastructure helped the organization phase out the complex on-premise solutions required to handle the huge data volume. Easy connectivity with the existing solutions used for data analytics practice and on the fly scalability of the computation layer helped the organization increase productivity. It also paves the way for seamless integration to the organization's architecture. The Data Marketplace of Snowflake ensured secure data sharing with third parties adhering to the GDPR policies. The in-built data security policies and features minimize the role of organizations to provide data privacy as well. This enables the organizations to make only those data points visible to end-users that they seemed apt for sharing. It also ensures that the data always resides in the organizational Snowflake database rather than on third-party databases. Moreover, the organizations could reach out to thousands of potential clients through Snowflake Data Marketplace without relying on any intermediatory sources. All this ultimately brings out the scope of using the existing data to drive revenue to the organization and highlights the importance of having a complete environment like Snowflake to capture, preserve, access, and transform data. Authors: Rahul Vijayan, Firdous Maqbool