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Cloud Data Warehouses - Apr 12 2021

The Avalanche Guide to Hybrid Data Analytics

Avalanche by Actian is one of the most popular hybrid data analytics solutions out there. In essence, it is a managed hybrid cloud data warehouse with excellent features and scaling capabilities. It also promises fast operation, the possibility of a diverse workflow, and major cost savings with respect to competing products. Here’s a quick guide.

What is a hybrid data architecture?

Hybrid data architecture is wherein data is stored and handled both in on-premise assets and in cloud assets. A lot of businesses have on-premise data storage and processing systems. A lot of businesses have their data entirely on the cloud. Hybrid architecture is an approach that integrates the strengths of both these systems. 

It is easy to understand the appeal of hybrid data architecture. If you have been relying on your on-premise data infrastructure, you are well-aware of the important benefits that come from it. In many cases, it’s a compliance demand. Plus, fast query speeds and minimal operational latency can really make for a great workflow. On the other hand, the cloud has a number of tried and tested benefits. The best way to combine them is to use hybrid data architecture.

Businesses often face problems adopting cloud technologies, especially if their on-premise systems are an integral part of their workflow. A hybrid approach can be of great help in such situations. This enables them to still make full use of the investments they made in order to set up their on-premise infrastructure while also embracing the latest technologies and creating new efficiencies.

There are various important advantages of embracing a hybrid data architecture. One of the main advantages is the fact that you can effectively eliminate silos from your organizations. On-premise data often resides in silos and brings in inefficiencies based on data duplication and reworking. With a hybrid architecture, silos are gone, and you have integrated data which can be centrally accessed. Also, since a hybrid data architecture allows for centralized access of data from disparate sources, this system is also excellent for better governance and security.

What are the top Avalanche hybrid cloud considerations?

There are several important considerations you have to keep in mind while deciding whether to move to an Avalanche hybrid cloud infrastructure. As always, it is crucial to look at the advantages of such a system and compare those with the unique needs and demands of your own workflow and look for points of synergy.

First, it is important to consider if you can benefit from a hybrid cloud implementation. You get to enjoy the benefits of the unique combination of on-prem and cloud platforms with a hybrid cloud system. This kind of system is particularly suited if you are working with high volumes of data stored at multiple locations, with a high volume of complex queries, and with a high number of concurrent users accessing the data. If your organization ticks all these boxes, then using Avalanche hybrid cloud can definitely be a consideration for you.

On top of that, you also need to consider if you need to use multiple cloud platforms like Google Cloud, Azure, and AWS. Ponder whether you need Avalanche with these considerations in mind.

What’s unique about data analytics on a hybrid data architecture?

There are several unique factors about data analytics on a hybrid data architecture. This kind of framework affords you several options that you would not be able to exercise otherwise.

First, if your analytics workload is heavy and dynamic, this infrastructure can have several benefits. You can choose to segregate your workloads based on several factors. For sensitive and less volatile workloads, you have the option of using your on-premise data centers or a private cloud resource while dynamic workloads that are less sensitive can benefit from an easily scalable public cloud. This is a good way to increase overall speed and also to protect more sensitive workloads.

Similarly, your Big Data analytics can also be segregated between a fast, scalable public cloud and a more secure on-premise data center. For security-focused and sensitive data, this provides you an added layer of protection while also allowing enough versatility to handle other data analytics operations as fast and efficiently as possible.

Another unique aspect of data analytics on a hybrid cloud platform is the fact that you can keep things flexible. You can gradually or incrementally move things to the cloud, setting your own pace. Meanwhile, your workflow remains intact and mission-critical data analytics can still be carried out with ease.

What is a data integration strategy?

In a nutshell, a data integration strategy dictates how to combine data from different, disparate sources in order to centralize access and gain better business insight. The merged data can be queried for real, actionable insight that can play a large part in deciding overall business plans and strategies. There are different data integration approaches that you can use to accomplish this.

What is the purpose of data integration?

The purpose of data integration is to make sure that data from different sources can be merged, located, cleaned, retrieved, and presented centrally with a high degree of speed and efficiency. Data generation and collection need a specific purpose and using that data effectively to generate insight is the priority for most organizations. This is where data integration can play a big role and decide the quality of insight you can get from your data.

What are the challenges of data integration?

There are several challenges associated with data integration. Most of them have to do with the approach or strategy you choose for the integration process. There are several directions you can go and each method has its own pros and cons.

For example, with a completely manual integration, there is great freedom and control over the integration process and costs can be significantly reduced. However, such an approach can also leave a lot of room for human error and prove to be quite difficult to scale. Similarly, while using an application-based integration strategy, the actual process becomes very simple with very little use of resources. But, this can lead to limited access to the process and create inconsistencies in the results as this approach is unstandardized to a great degree.

Whichever approach you choose, there would be challenges to negotiate. The best you can do is to use a method of integration that brings the most benefit with the least pitfalls.

Do I need an Avalanche service provider near me?

Adopting a solution like Avalanche can involve a lot of planning and hard work. You need to know the unique features and benefits of the platform and juxtapose them with your use case to make a smart decision. Then comes the deployment and the transition. All of this can become a lot easier with a helpful Avalanche service provider near you, like NextPhase.ai.

Have questions? We help companies like yours, every day.

Email us at hello@nextphase.ai

Read More

The Guide to Avalanche Cloud Data Warehouses

About NextPhase.ai

NextPhase.ai is a cloud data management and analytics services provider. For 10 years, we’ve helped global companies harness the power to turn data into insights that drive growth. Whether you’re migrating to the cloud or implementing a cloud data warehouse, contact us to schedule a workshop.

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