Three ways to leverage the private cloud for flexible data warehousing

Director Hybrid Data Management, IBM Analytics

At a time when data and associated analytics requests are growing by leaps and bounds, data warehousing is no longer a one-model solution. Why? As you address rising varieties of data and user and application requirements, you need a flexible range of solutions to run your analytics.

Some analytics are on the cloud, and some analytics are on premises. A big data vendor manages some analytics, and you manage some of them. And as if that variety is not challenging enough, your users don’t want to be bothered with the topology and characteristics of the underlying data stores.

From an IT standpoint, you are in charge of providing analytics solutions to your clients. With all these new requests, your responsibility increases and the factors influencing your decision grow by an order of magnitude. One option is a private, client-managed cloud solution that can deliver simplicity with increased levels of flexibility.

Fast, dynamic cloud-based deployment

A private cloud solution allows for more isolation at a lower level of the infrastructure stack to achieve highly predictable and repeatable results, and satisfy specific data handling requirements. Client-managed cloud solutions also enable fast, dynamic deployment of new workloads and insulate users sharing the same cloud infrastructure. And they can help improve return on investment (ROI) by providing a high level of hardware utilization with less administrator involvement at the application level. The choice of data warehousing on a private cloud comes down to flexibility and control in three key areas.

1. Increased control over data and applications

Platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS) offerings exist because clients want more control than they currently have over their service platform, while benefitting from easier and more economical infrastructure management than ever. IBM SoftLayer provides an example in which you can select the services and options you need, from servers to virtualization software to networking, security and more. Cloud requirements tend to vary by customer, and these solutions give you the control to build a solution that meets your specific needs.

For data warehousing, you may already have a strategic cloud-based infrastructure and wish to leverage it to run your data warehouse in this environment. IBM recognizes this need and has developed IBM dashDB Local, which offers advanced dashDB data warehouse technology to be deployed on premises or on a hosted IaaS by leveraging Docker container technology for fast and simple deployment and updates. And because Docker is broadly supported, you can move your warehouse environment from an on-premises to a hosted infrastructure—or vice versa—according to your needs and comfort.

2. Tight management and monitoring

Along with tight control comes the need for you to manage the solution. When you are using IaaS, you can address the specific monitoring, governance and compliance needs of your business. If there are specific service-level agreements (SLAs) that govern your data warehousing and analytics services, dashDB Local gives you the elasticity and control to scale up, out or in as needs change. If you face data governance mandates that, for example, require data to stay on premises, then dashDB Local brings the technology to your environment. If you want to manage your private cloud in the same way as the rest of your infrastructure, you can deploy the right agents to these solutions and get a holistic view of what is happening across your architecture.

3. Solutions built for user requirements and self-service applications

Any data warehouse or analytics solution is ultimately about providing a business service. The ability to get the answers to their questions quickly motivates users and enables them to drive business value. And they prefer to avoid handling the technology if possible. As a result, you need to quickly stitch together an integrated solution such as IBM Cognos Business Intelligence (BI) as a front end and dashDB Local as the data warehouse. When you create key solutions such as this one, you can offer them in a service catalog. Data scientists and other users can select and dynamically provision them through your IaaS as self-service options. And you can include a preload offering of well-defined data sets, if you like.

A self-service approach can improve business agility and reduce dependency on IT. It empowers your line-of-business clients and allows you to focus on other IT requirements and goals.

Agile data access and autonomous infrastructure control

Overall, cloud infrastructures offer a range of options that can help you improve agility, address the unique needs of your business and enable you to deliver enhanced business value. dashDB Local recognizes and addresses the needs for flexibility, and it takes the data warehouse to specific infrastructures quickly and easily while keeping you in control.

The dashDB Local offering began a closed preview program in February 2016. We have received enthusiastic feedback from preview participants, including many comments that it is fast, easy to install and runs quickly even under growing data volumes. Learn more by getting started with dashDB Local to see how it can help you meet specific needs and help us shape the solution.