Battling the extreme climate of data growth
Big data – the hot IT buzzword dating back to 2012, is a pretty nebulous term, in the same way that ‘cloud’ covers diverse technologies. Input data to big data systems includes information from social networks, web server logs, traffic flow sensors, satellite imagery, broadcast audio streams, banking transactions, the content of web pages. The list goes on.
Taming big data
Data is often too big, moves too fast, or doesn’t fit the strictures of database architectures. Thus, a well-planned strategy for data placement, mobility, and ingestion is the only way to keep up with the incessant data growth. More importantly, how do you harness the valuable patterns and information available from processing it? A helpful way to consider the challenges is the 4 Vs of big data – volume, velocity, variety and veracity.
The tighter the feedback loop, the greater the competitive advantage. The results might go directly into a product, or into dashboards used to drive decision-making. It’s this need for speed, particularly on the web, that has driven the development of key-value stores and columnar databases, optimized for the fast retrieval of precomputed information.
The Challenge of Velocity
With the multiple new applications and dynamic workloads we face in the Information Age, there is a need for a workload optimized sub-infrastructure: an IT environment that looks at individual workload characteristics, enhances ease of management, and recognizes the different operational criteria for each one, is the key to moving towards workflow-optimization and architectural freedom.
It becomes evident that there are two main reasons to consider the streaming processing. The first is when the input data is too fast to store in its entirety: in order to keep storage requirements practical some level of analysis must occur as the data streams in. The second reason is where the application mandates an immediate response to the data.
The internet and mobile era means products and services increasingly generate a data flow back to the provider. Those who are able to quickly utilize that information gain a competitive advantage. The smartphone era increases again the rate of data inflow, as consumers carry with them a streaming source of geolocated imagery and audio data.
Boosting storage velocity through performance, efficiency, flexibility
Keeping critical business applications running at a fast clip is often the most important job for a storage platform. Companies rely on OLTP systems for business-critical activities in a variety of areas including finance, ecommerce, and customer relationship management (CRM). They can’t afford to deliver a sluggish experience to their users.
When selecting enterprise-class storage, companies seek a platform that delivers strong application performance while using capacity efficiently. They also look for an underlying architecture that offers flexibility as their needs evolve, and a graphical user interface (GUI) that simplifies routine tasks.
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With Dell Technologies’ extensive data storage portfolio, negotiating the scope of insights and innovation becomes a less daunting task. Find insights faster and shift an extra 12% of IT staff to innovation. Optimize any workload at scale to accelerate analytics workload performance up to 78%. Cut application outages and latency issues by 90%, while reducing storage requirements and network loads, with advanced storage and deduplication.