Like a busy airport, a data analytics platform in the cloud should be a hub for connections both near and far.
More specifically, it should function as a centralized, highly connected location for analytics workloads that originate from multiple data sources, pipelines and cloud computing services (e.g., AWS, Microsoft Azure, Google Cloud, etc.). It should provide the infrastructure and processing power to help such workloads reach their “destinations” — i.e., of becoming consumable insights for enterprises and their stakeholders.
But even though the cloud itself offers much greater agility, flexibility and scalability for analytics than is achievable on-premises, optimizing an analytics strategy for the sheer volume of data and variety of different cloud services in play is challenging without the right setup — namely, a connected cloud.
What is a connected cloud?
A connected cloud is a data platform that tightly integrates multiple cloud computing services — along with their respective storage solutions, plus connected data sources and pipelines of any type — into a performant, cost-effective and synergistic whole. With a connected cloud architecture, enterprises get more holistic and intelligent analytics.
Open APIs, playbooks, SQL engines, and a data fabric make a connected cloud the go-to platform for gaining insights into a business. It’s built for cloud analytics workflows of any kind, using deep connections to customer cloud environments and flexible, powerful query processing.
Connected cloud in the context of cloud computing
Connected cloud is vital in a multi-cloud world. To see why it’s useful, let’s quickly define both cloud and multi-cloud and where the two fit into analytics strategies:
Cloud: Pooled compute, storage and network resources, accessible on-demand over a network. For analytics purposes, cloud solutions are ideal for handling the vast amounts of data that now flow in from numerous sources, for example, suppliers and customers.
Multi-cloud: The use of cloud services from more than one cloud provider. Multi-cloud enables enterprises to pick and choose a best-of-breed solution for each use case, avoid vendor lock-in and negotiate the most economical rates, among other benefits.
Indeed, per a 2020 IDC estimate, over 90% of enterprises are on their way to consuming cloud services from multiple cloud providers, ranging from compute infrastructure for CPU-intensive workloads, to object storage solutions capable of supporting any type of application. The core value proposition of a connected cloud is the ability to pull any workload from any of these integrated major clouds and then transform it into actionable analytics.
Another way to think of it: Connected cloud is the nerve center for all multi-cloud analytics workloads. Regardless of the data source, pipeline, storage service or cloud provider used, the connected cloud has the performance and security to deliver clear insights. It may also connect to existing on-premises architectures as part of a hybrid multi-cloud setup.
Four big building blocks of a connected cloud
Just as an airport interconnects numerous routes and carriers, a connected cloud does something similar for each cloud service and solution that supports an enterprise’s analytics strategy. It works with:
1. Multiple cloud service providers
Whereas point/cloud-specific solutions are each optimized for a single service provider, a connected cloud works with all of them. No matter which cloud computing platform or cloud application an enterprise uses, the core technology of a connected cloud can integrate with it.
2. Diverse data sources
In addition to the major cloud providers themselves, a connected cloud also connects to data sources such as databases, flat files, CRMs, ERPs, SaaS cloud apps and streaming engines.
3. Numerous data pipelines
Data pipelines help automate the processing and movement of analytics data at scale. Solutions such as AWS Glue, Azure Data Factory and Google Cloud Data flow can be plugged into a connected cloud for extract, transform and load (ETL) workflows.
4. Different cloud storage types
Enterprises often collect immense amounts of unstructured data from devices like IoT sensors and then put it into a data lake or cloud object storage repository. Connected cloud can bring all of this storage closer to compute capacity, to enable elastic scaling while still keeping storage and compute separate.
How a connected cloud transforms your data
Seamlessly connecting the above components and all the enterprise data flowing through them is one of two core advantages of a connected cloud. The other is the ability to transform that data into valuable analytics.
The connected cloud manages all of the above cloud ecosystem connections using technologies such as its built-in SQL engine, data fabric, open APIs, and broad programming language and tool compatibility. For instance, its data fabric can connect different analytics environments and standardize query processing across them.
Likewise, a connected cloud solution like Teradata Vantage can also ingest data of virtually any type or format, whether it came from a company’s ad campaigns or its warehouse sensors, and scales its processing. In this way, a connected cloud extends the overall advantages of multi-cloud environments by:
Enabling enterprises to use the clouds and analytics ecosystems of their choice.
Giving them the flexibility to find optimal solution pricing and avoid lock-in.
Accelerating their time to insight by reducing data performance and synchronization issues.
What are the benefits of a connected cloud?
Let’s dive deeper into these benefits. Using a connected cloud, an enterprise can overcome some of the challenges that might otherwise arise when trying to get the most mileage out of their analytics. These hurdles include:
Achieving consistent performance across clouds
Because of the laws of physics, cloud computing infrastructure and any cloud app won’t match the performance of an on-premises equivalent, all else being equal. Distance leads to latency. And there’s also enormous variety in data types. Accordingly, enterprises need consistency — and a connected cloud provides the connectivity, security and querying capabilities to make it happen.
Avoiding a patchwork of cloud-specific point solutions
When mixing and matching cloud services, an enterprise might use each cloud provider’s own data platform. But doing so can trigger its own issues, in the form of needing point solutions to plug in any gaps across multiple clouds. One cloud’s data platform won’t be compatible with another’s, while the resulting point solutions only increase complexity and create data silos.
Eliminating data silos and data drift in analytics
Speaking of which, the upkeep of multiple disconnected data solutions can result in data silos that aren’t synchronized across cloud computing environments. This disconnect hinders decision-making: In a 2020 Exasol survey, almost 60% of organizations admitted making decisions based on outdated information.
Striking a balance between basic and advanced analytics
A connected cloud provides greater consistency and flexibility than a data solution limited to a single cloud or type of analytics workload. Accordingly, it can address a wide range of potential enterprise needs, from basic data warehousing built on easy-to-use solutions and pay-as-you-go cloud services, to more advanced analytics bound to SLAs and predicable pricing.
Managing and optimizing cloud spend
Avoiding overspending in a multi-cloud setup can be challenging. This is primarily due to the variety of workloads, some of which may fluctuate significantly in the amount of cloud computing resources they utilize, while others remain more or less constant. A connected cloud can support finding the right cloud services for these differing situations, and enable:
Consumption pricing for on-demand resources, so that an enterprise only pays for what it uses — ideal for workloads with high variability.
Blended pricing, which mixes reserved and on-demand pricing — a good fit for consistently high utilization.
A combination of these two pricing models.
Going beyond the limitations of an on-premises environment
A connected cloud provides a path beyond the data center. Enterprises can connect their existing data center investments and tools to a connected cloud architecture, or decide to get out of the data center business altogether and pursue a full multi-cloud strategy. In either case, the connected cloud can be the hub for all of their analytics workloads.
Teradata and the connected cloud
When it comes to the connected cloud, Teradata does it all.
The advanced SQL engine and frictionless ETL processing of Vantage can accelerate your multi-cloud journey, by yielding the actionable insights you need for your operations, from any cloud service and analytics architecture. Connect with our team to learn more about how we can help.