Analytics is the driving value behind data. It provides leaders and users with the critical information they need to stand out from the competition, create innovative products and services, and deliver more worth to their customers.
In recent years, analytics evolved from descriptive to prescriptive to provide organizations with more business value. Users can now use analytics to accelerate forward-looking decision-making. However, this increase in analytics means that companies need more data than ever. Previous methods of modifying data and data transfer slow down enterprises and incur enormous costs. Organizations need faster access to massive data sets than they had in the past.
Read on to see how organizations can improve their data transfer to kickstart their analytics and get more from their data.
No Data Left Behind
To make the future of analytics possible, organizations need to retain most (if not all) of the captured data. They also need to move it to the right cloud or data center rapidly so applications can process it and provide free and easy access to all stakeholders at any time. Enterprises need more out of their data than in the past, but too often, traditional data movement models hold them back.
Many organizations resort to data modification technologies (such as encryption) and data manipulations (such as compression) to protect and move data when connections are not ideal. This helped them overcome some data weaknesses for a while, but as new requirements emerge around data sets, these too often fall short.
Organizations require raw data to serve new uses and power analytics with full data sets in addition to a compressed sample. Enterprises across all verticals require more than one way to move data to accommodate the emerging needs of users: the first for compressed and modified data sets, while another provides every byte to migrate back into data centers or public clouds. It requires a balancing act between accelerating data access and incorporating all data so that none is left behind.
To face these challenges, IT must deploy processes and tools that enable data managers to move data rapidly with no demand between locations for multiple purposes, from endpoint capture to edge and core data centers to numerous cloud sites. Companies take various approaches to try to make this happen when transferring data. Each has strengths and weaknesses, depending on the scenario.
Moving Data Faster and Moving More Data (or All Data)
Wireless networks are popular for transferring from endpoint to edge data centers. They are widely available, always on, and competition means that organizations have several great options. However, mass data bottlenecks and reliability issues mean that many enterprises face potential delays. Plus, the fixed price model means organizations pay for connections even if they haven’t used them. Other companies use wired last-mile connectivity for their endpoint-to-edge transfers to overcome reliability issues. However, it isn’t universally available, and performance can suffer in some U.S. states. It also often comes with a hefty price tag regardless of use.
Because large amounts of data accumulate at the edge data centers, many companies periodically turn to wired middle-mile infrastructures to move them to the core data centers. They struggle to get performance and reliability, though. The technology also comes with major price considerations, either as an up-front cost or multi-year leases that can quickly get out of hand.
In the final stage, edge-and-core-to-cloud data transfers come with challenges for most companies. Cloud technology offers enterprises mass data transfer functionality that provides them security, reliability, and granular control. Over time, though, organizations discover unplanned and complicated costs when moving data to another storage type or cloud.
Many organizations turn to physical mass data transfer to avoid unnecessary costs. Instead of relying on wireless or wired data transfer, they use data transfer devices to move it to a destination, such as a core data center or cloud provider. From there, data is removed and shipped back to reuse.
External drives are one option that comes with 8-16T capacity. Because they are consumer-focused, they often lack the security, scalability, performance, and ruggedness required for an organization. Cloud vendor data transfer devices are more commercially focused and keep the needs of enterprises in mind. They are secure, portable, and ruggedized, but organizations who use services tied to a single cloud provider risk vendor lock-in. Also, many vendors don’t support bi-directional transfers, and have complicated pricing structures and extra fees that could be challenging to fit in a budget.
To solve for these weaknesses in data transfer processes Seagate offers a unique enterprise data transfer as a service called Lyve Mobile. Suites of enterprise data shuttles have variable capabilities to best meet the needs of businesses that need to perform mass data transfers regularly. With up to 96TB per device and 22GB/s throughput, enterprise data shuttles have high capacity and performance while providing a simplified, rugged, and cost-effective model. Plus, the open infrastructure prevents lock-in to help organizations build a best-of-breed infrastructure.
There is no one-size-fits-all answer to data transfers. Most organizations have a variety of methods and use different ones when specific situations arise. Being aware of the strengths and weaknesses of each one equips businesses to make better decisions with their data. Read Seagate’s Enterprise Data Transfer Playbook to learn more about the options.
Keeping Control of Your Data: Multicloud Flexibility
As IT and business leaders seek to extract value from legacy data and analyze new data for insights and new revenue streams, massive data growth is a challenge. In addition, powerful business tools such as Internet of Things (IoT), AI, and machine learning (ML) require significant amounts of data, and their use is only predicted to grow. A multicloud strategy strengthens organizations’ ability to access and leverage mass data for analytics freely in the face of growing need for data. However, this flexibility, freedom, and innovation often mean cloud costs spiral out of control.
The multicloud complexity can exacerbate efforts to access data easily and move it quickly for different analyses. Seagate’s recent Multicloud Maturity Report, which surveyed 500 senior IT leaders, software development, and data analytics, found that many businesses today face significant hurdles in leveraging their data. Most are due to friction in today’s multicloud paradigm:
- 82% already use at least 2 public cloud infrastructure service providers. This number is expected to increase to 93% in two years.
- 76% said monitoring, measuring, and ensuring service-level agreement adherence for intercloud integrations is difficult.
- 84% agreed that there were opportunities to better leverage existing data in their organization.
- 73% said that data retention costs hampered their ability to maximize data value.
Data freedom and sovereignty are critical to sharing and leveraging data freely. Organizations need control of where they put their data and early get it into and out of wherever it needs to be located. It is vital for companies to power analytics and ensures their business tools have the data they need to fuel insights.
Because data use is evolving and impossible to predict, they need a straightforward cloud storage platform like Seagate’s Lyve Cloud to tell them their storage and data access costs from the outset. Data analytics relies on access and different uses, so leaders should seek a data-centric cloud that doesn’t charge egress fees to move their data outside that cloud.
Kickstarting Your Analytics Will Lead to Better Business Outcomes
Data does not exist in a vacuum. Its value is in creating insights to improve business outcomes. Organizations that can harness their data into detailed analytics that speed decision-making will reap the most benefits from their information and data costs.
According to Seagate’s Multicloud Maturity Report on the challenges of managing and leveraging the value of mass data, organizations that strengthened their data strategies and cloud architectures kickstarted their data analytics. They harnessed the value of their data and are reaping meaningful business results:
- Grew data-related revenue 57% faster than their less mature peers
- Launched 2.5× as many products and services that relied on data innovation in the last 12 months
- Were 2.6× more likely to state that their product innovation drove higher customer satisfaction scores
- Were 6.3× more likely to go to market months or quarters ahead of their competition
Analytics is crucial for staying competitive in a digital world. Organizations must improve their freedom and flexibility to keep up and drive innovation in the modern marketplace.
Click here to learn more about data management and movement processes to help kickstart your analytics and get more value from your data.
To explore ways successful organizations have managed their cloud or multicloud architecture to start getting more value from their data and analytics, check out Seagate’s Multicloud Maturity Report.
