At Contexti, we’re always looking for new ways to make it easier to work with data.
When it comes to Big Data projects, it’s all about efficiency. We’ve rounded up the five best tips on how to make it happen.
#1 – DATA COMPRESSION
This can be a great way to reduce repetitive information, have shorter transition times and free up some storage space. The process of encoding data more efficiently to achieve a reduction in file size can happen in two ways: lossless and lossy compression.
“Lossless compression algorithms use statistic modeling techniques to reduce repetitive information in a file. Some of the methods may include removal of spacing characters, representing a string of repeated characters with a single character or replacing recurring characters with smaller bit sequences.” – Conrad Chung: Customer Service & Support Specialist at 2BrightSparks.
The great thing about lossless compression is that no data is lost during the compression process. With lossy compression, data such as multimedia files for images and music can be discarded. Lossy compression on the other hand, works very differently.
“These programs simply eliminate ‘unnecessary’ bits of information, tailoring the file so that it is smaller. This type of compression is used a lot for reducing the file size of bitmap pictures, which tend to be fairly bulky.” – Tom Harris: Contributing writer at HowStuffWorks.
#2 – CLOUD OPTIMISATION
“If your organisation wants to extract the highest level of application performance out of the computing platforms that it purchases, you should ensure that workloads are optimised for the hardware they run on.”- Joe Clabby: Contributor at TechTarget.
Choosing the right cloud services to achieve this requires consideration of efficiency, performance and cost advantage. A great tool for workload optimisation is the Cloudera Navigator Optimizer for Hadoop-based platforms.
“Cloudera Navigator Optimizer gives you the insights and risk-assessments you need to build out a comprehensive strategy for Hadoop success.” – Cloudera Inc.
Not only does it reduce risk and provide usage visibility, it’s also flexible and keeps up with changes in demand. “Simply upload your existing SQL workloads to get started, and Navigator Optimizer will identify relative risks and development costs for offloading these to Hadoop based on compatibility and complexity.”
#3 – UNIFIED STORAGE ARCHITECTURE
Many enterprises experience the same dilemma: unified storage system or traditional file/block storage system?
Randy Kerns, Senior Strategist & Analyst at Evaluator Group describes unified storage as “ A system that can do both block and file in the same system. It will meet the demands for applications that require block access, plus all of the file-based applications and typical user home directories you have.”
With the ability to simplify deployment and manage systems from multiple vendors, unified storage architecture is growing in popularity among storage administrators who are quickly seeing the benefits of the distributed access and centralised control it provides.
An article in TechTarget highlights the key benefits of running and managing files and applications from a single device: “One advantage of unified storage is reduced hardware requirements. Unified storage systems generally cost the same and enjoy the same level of reliability as dedicated file or block storage systems. Users can also benefit from advanced features such as storage snapshots and replication.”
#4 – DEDUPLICATION
“Deduplication is touted as one of the best ways to manage today’s explosive data growth.” – Brien Posey: Technology Author at TechRepublic.
Data deduplication is a technique of eliminating redundant or duplicate data in a data set and as a result, maximising storage savings and increasing the speed and efficiency at which data is processed.
By reducing the amount of storage space an organization needs to save its data, you’re not only saving time and money, but you’re preserving the integrity and security of of your data. “The simple truth is that to be effectively managed, adequately protected and completely recovered, your data size must be shrunk.” – Christophe Bertrand: VP of Product Marketing at Arcserve.
Here’s how it works: “Each chunk of data (e.g., a file, block or bits) is processed using a hash algorithm, generating a unique number for each piece. The resulting hash number is then compared to an index of other existing hash numbers. If that hash number is already in the index, the data does not need to be stored again. Otherwise, the new hash number is added to the index and the new data is stored.” – TechTarget.
#5 – CROSS-CHANNEL ANALYTICS
“Cross-channel analytics is a where multiple sets of data from different channels are linked together and analyzed in order to provide customer and marketing intelligence that the business can use. This can provide insights into which paths the customer takes to conversion or to actually buy the product or avail of the service. This then allows for proper and informed decision making to be made.” – Techopedia.
Among the many benefits of this process are understanding the impact of each channel, how they work together and determining which channel combinations get the highest results and conversions. It’s an efficient system that generates insights useful to each department within your organisation.
“Business leaders can use this information to design better process flows for customers by creating or revising customer journey maps. Meanwhile, marketers can use behavioral data from customer interactions in different channels for other purposes.” – TIBCO Blog.
For more resources, please see below:
Unified Storage Architecture