An architect's guide: How to use big data
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What are some of the biggest challenges organizations face with application development, incorporating in-memory data grid technologies, and the middleware environment?
Many organizations find that their existing IT environments are not able to adequately support evolving requirements for speed, flexibility and performance. Business environments are changing so quickly that many companies find they can't keep up with client demands without rethinking some of their traditional approaches to managing IT. Business decisions increasingly need to be made in real or near real time, which has an impact on everything from data management to application performance.
One of the major issues for companies is the need to store, access and analyze larger volumes of data at much faster speeds than ever before. In fact, it is not just large volumes of data, but also the need to manage larger and more diverse varieties of data, including unstructured data. This can be a real challenge in companies with IT environments that were designed to support many different types of workloads that were often managed as individual siloes. Most of these systems were designed for an earlier time when changes occurred less infrequently than they do today. In order to remain competitive and manage customer expectations, companies find the need to introduce new and innovative applications very quickly, and these require frequent upgrades and changes.
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What's so hard about keeping up with customer expectations in a very fast-paced business environment? Companies need to manage their siloed IT environments in a more holistic way. Typically, IT systems were not designed with the speed and scalability to manage the large volumes of data and varied sources and varieties of data that are needed to support today's complex applications. There are many different approaches that companies can take to support this need for speed and flexibly.
In terms of big data, in some cases it's figuring out what is and what isn't working in your current environment -- and data grid technologies can help. For example, you may have adjusted the way you use your traditional relational database environment to support your business processes. In some cases, you may make changes that really go beyond the capabilities of your database environment. You need to figure out the best approach moving forward and the best role for data grid technologies in your environment. Will they be used for data storage or will they be used to increase speed?
This transition doesn't necessarily happen in a day. A lot of it has to do with your existing business process and understanding where the limitations or bottlenecks are in your existing environment. Now, IT needs to take some time to figure out the major requirements moving forward. Sometimes a customer needs some ongoing support to make sure the transition to implementing data grid technologies into its environment goes smoothly.
About the author:
Marcia Kaufman is the COO and founding partner of Hurwitz & Associates. She specializes in the customer benefit of enterprise and emerging technologies, information management and service oriented architectures.
Editor's note: This expert advice is taken from an interview by associate editor Maxine Giza.
Marcia Kaufman asks:
Meeting which of the following requirements has been most difficult for your organization?
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