Big data has quickly cemented its place as one of the most important, valuable resources that companies of all kinds can potentially leverage. This is all thanks to the evolution of big data analytics technology, which allows firms to transform otherwise unusable unstructured and semistructured data into actionable insight. This information can provide a tremendous advantage for firms as they climb to the top of their industries.
Developing and maintaining an effective big data analytics program is therefore critical for a huge range of companies. Yet to achieve this result, companies must account for a number of different factors.
One of the most significant of these is data storage. After all, organizations must find a place to hold all of the massive data required for effective analytics. Yet what is the most efficient means of handling storage?
For many firms, the answer is cloud-based storage; more specifically, Amazon Web Services' recently launched Redshift data warehouse. This solution can help many companies to meet their big data storage needs with a cloud environment.
Big data storage
Cloud-based big data storage is highly valued for a number of reasons. Most notably, information in the cloud is immediately accessible by all authorized personnel within a company, regardless of time or place. This eliminates one of the most significant challenges firms face regarding big data analytics: ensuring that the resource is available to essential personnel as needed.
If a company maintains a half-dozen locations throughout the United States, for example, and each one creates, accumulates and analyzes big data, it will be extremely difficult, if not impossible, to share the data effectively when using legacy on-premises solutions. These systems cannot handle the demands of big data, leading to delays and compromising the accuracy and worth of the big data accessed.
Storing big data in the cloud overcomes this issue. And Amazon's Redshift represents the most viable option for cloud-based big data storage yet developed. Redshift offers storage at one-tenth the cost of traditional warehouse systems, and can be customized to meet the needs of just about any company, whether it requires a few hundred gigabytes of storage or more than a petabyte.
However, as useful as Redshift is, the solution is only a viable option for firms that invest in the tools necessary to leverage it.
Big data movement
However, there is a problem. Namely, most big data is generated on-site. Firms looking to utilize cloud-based storage, such as Redshift, must therefore transfer files to the cloud. This presents a problem similar to the one experienced by companies relying on legacy big data sharing tactics: without a dedicated solution, inefficiencies and delays will undercut the value of the data.
Companies looking to leverage Amazon Redshift must therefore invest in tools that can effectively upload thier database to the cloud.
One of the best options in this regard is Attunity CloudBeam. Attunity CloudBeam represents one of the most effective, sophisticated solutions available for on-premises cloud upload, and is specifically designed to work with Amazon Redshift. CloudBeam features guaranteed transfer reliability, is easy to manage and supports a variety of data sources, including Microsoft SQL Servers and Oracle.
With CloudBeam, firms can easily transfer cloud-stored data from one environment to another, providing a maximum degree of flexibility. Additionally, CloudBeam is secure, featuring strong encryption protection for all data in transit.
By leveraging both Attunity CloudBeam and Amazon Redshift, companies can optimize their overall big data analytics systems for the greatest value gains possible.