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Big Data Analytics Selecting the Right Pond to Catch Big Fish
"The world's first god of marketing, Jay Abraham's book, "Pick the Right Pond to Catch the Big Fish", describes different customer groups as fish, and the collection of different customer groups is a different pond, and companies should think about how to quickly find target customers with the help of a pond that has already been established from someone else, based on their own target customers."

Big Data Analytics Challenges UnlimitedGartner survey shows that: 55% of organizations are implementing big data solutions to enhance customer experience, 49% of organizations use big data solutions to improve process efficiency; 42% of enterprises are looking for new products, establish new business models. However, big data analytics is a major challenge for organizations today, as they not only need to manage the ever-growing amount of native data; moreover, in the highly developed Internet of Things (IoT) today, the huge amount of data comes from different sources, some from sensors, mechanical devices, and some from social media, etc., and the variety of sources of data has erected a barrier to big data analytics in the enterprise.

The condition for solving the above problems is that enterprises must choose the right big data analytics platform, i.e., choose the right pond, only then can they fish out the "big fish" in a small amount of data.

Dell Cloudera Data Analytics has everything when it comes to big data analytics, and there's no doubt that Hadoop is the most popular data analytics platform for businesses. However, the installation, configuration and operation of Hadoop clusters have many places that require careful consideration. Such as software, how to choose the right Hadoop distributed and scalable software and monitoring and management software? On the hardware side, how to distribute the physical nodes of Hadoop services? How to choose the right server? In terms of functionality, how is the performance and scalability of the Hadoop platform? And so on.

In response to this series of problems with Hadoop, Dell and Cloudera launched the Dell Cloudera Big Data Solution.

Dell Cloudera provides everything you need for Hadoop, including hardware, software, resources, and services. Using this solution helps users to easily solve various problems related to Hadoop deployment, management, and other issues, and quickly extract value from massive amounts of data.

Dell Cloudera both hardware and softwareDell Cloudera is a reference architecture consisting of Cloudera services as well as the Cloudera management suite that enables open source Hadoop to run efficiently in data-driven enterprises in production environments.

Hardware results in faster processingHardware, Dell's PowerEdge C2100 rack servers and PowerConnect 6248 Ethernet switches have been used successfully in big data deployments, and the Dell Cloudera solution is based on this component.The Dell PowerEdge C2100 servers allow users to both memory and disk capacity, and it is specifically designed to maximize space, power and cost efficiency in the data center. Where the density of memory and storage is critical to the data center, the PowerEdge C2100 accommodates 18 DDR3 memory slots and supports up to 144GB of memory capacity, so businesses can get data analytics results faster. Meanwhile the PowerEdge C2100 rack server provides memory as well as disk for MapReduce, Web analytics and databases. In addition, the Dell PowerConnect 6248 offers a full 48 Gigabit Ethernet and Layer 3 switch to support more efficient rack densities as well as advanced features for core switching.

Software Hadoop management for more transparencyThe software side of the equation delivers high visibility within and between Hadoop clusters. Dell Cloudera allows Hadoop maintainers to accurately deploy and manage cluster resources in an efficient manner through a combination of expert support and software that delivers transparent management control. At the same time, Dell Cloudera allows business metrics similar to modern IT management to run Hadoop clusters in production environments at an affordable cost, optimizing resource utilization. Its built-in predictability anticipates changes to the Hadoop infrastructure, ensuring operational reliability.

In addition, Dell provides services and support for Cloudera Big Data solutions. It ensures that enterprise solutions are supported by specialized hardware and software teams that are tailored to the specific needs of the organization.

Dell Cloudera in-memory big data solutions for the amazing performance of Dell China and SAP China for an oil customer in the SAP HANA database + Compellent storage all-flash technology BI analytics system performance:

Star model design, including 2 fact table data, detail data model, indicator summary model?6 dimensional table data , number dimension table, ID dimension table, organization dimension table, personnel name, third-level unit name, branch name? The main table contains 18 billion records, data analysis volume of more than 60TB capacity!

The original system, more than 2 hours to calculate the results, and prone to interruptions ...... using Dell Compellent storage all-flash technology in SAP HANA's new business intelligence architecture, a single query shortened to less than 20 seconds, 400 concurrent query operation shortened to less than 10 minutes.

Dell itself is a user of this in-memory "big data" solution for in-house "precision marketing" intelligent decision-making and analytics systems. In 2015, Dell was honored as the first place winner of the SAP HANA Innovation Award-2015.

Conclusion "Fish swim and opportunities change, we must constantly change our position to find the big fish and cast the bait to catch them when they are hungry." -- "Pick the Right Pond to Catch the Big Fish"

In this age of data disrupting everything, companies' data is constantly changing, and companies have to pick the right data analytics platform for them with an evolving vision. Picking the right platform is the only way to catch the big fish - the big value - under the data pond.