Gartner defines Big Data as “high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making”.
Big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods.
The term covers each and every piece of data your organization has stored till now. It includes all the data stored both on-premises or in the cloud. It could be papers, digital, structured and non-structured data within your company. Read more →
One factor which plagues your AWS monthly bill is the amount spent on dealing with Big Data workloads. Amazon Web Services offers a solution with the launch of two new low cost volume types for its Elastic Block Store (EBS) service that are powered by traditional, spinning disk hard drives.
The new Throughput-Optimized HDD and Cold HDD EBS volume types let companies store files cheaply in a way that’s still useful for big data workloads like MapReduce and Kafka. The Throughput-Optimized service is aimed at apps that use data frequently, while the Cold HDD service is built for applications that reference items less frequently.
Amazon’s interest in EBS began in 2008, with continued innovations which allow customers to optimize their storage performance and cost for a wide range of workloads.
In 2012, AWS began offering Amazon EBS volumes that incorporated advances in SSD technology to deliver high-performance persistent storage for latency-sensitive transactional workloads like databases that require consistently high input/output operations per second (IOPS).
Snapshot of the new storage volumes:
You can get more information from the official Amazon website about the EBS Throughput Optimized HDD (st1) and Cold HDD (sc1) volumes, visit http://aws.amazon.com/ebs.
Amazon Web Services offers customers predictable performance for throughput-intensive and big data workloads with large data sets, large input/output (I/O) block sizes, and sequential I/O patterns.
Amazon EBS customers pay only for the storage they provision, with no additional charges for throughput, and prices start at $0.025/GB month.
Both these EBS storage volumes deliver low cost HDD storage with the predictable high-throughput required to meet the processing needs of big data applications.
Throughput Optimized HDD (st1) volumes include a maximum throughput up to 500 MB per second per volume and Cold HDD (sc1) volumes have a maximum throughput of 250 MB per second per volume.
All EBS volume types offer durable snapshot capabilities and are designed for 99.999 percent availability.
Customers can now call on a new 80TB Snowball storage appliance, along with the already existing 50TB Snowball to ship their data securely from on-premises servers to Amazon’s.
Users who don’t have Snowball-sized amounts of data to move, can opt for the S3 Transfer Acceleration service, which is designed to get moderate amounts of data transferred quickly into the AWS Simple Storage Service (S3).
It uses the AWS edge network, which is also used for Amazon’s Cloudfront CDN and Route 53 DNS service, along with optimized network protocols, to let users upload files to S3 up to 550 percent faster than they’d be able to with a straightforward data transfer.
These storage service moves are going to help Amazon customers get data into the cloud faster, which is particularly important for companies undergoing cloud migrations.
Sysfore can help you implement the new Amazon EBS storage volumes for your business. You contact us at info@sysfore.com or call us at +91-80-4110-5555 to know more.
Take the guesswork out of fashion. Big Datais your latest and hottest trends that’s taking the world of fashion by storm. In an industry where every color, cut, design and trend is micro analyzed and just as easily thrown out of the window with the next launch; you need to keep one step ahead of the competition. This is where Big Data puts its best foot forward (pun intended!)
Fashion as an industry is often regarded as frivolous or unnecessary, despite its global and money making capacity. But behind the scene is a very big business that can push the economy. The last projected revenues is around $3.75 trillion in 2016.
Big data solutions are increasingly become a part of the designers strategy. In an industry based on creativity, intuition and expression, applying cold data seems farfetched. But it is precisely this that helps the designers and retailers to accurately predict the latest fashion trends.
Big Data is all about turning extremely large quantities of data into useful information. When companies aggregate data and analyze them effectively, patterns emerge, ideas are born, and fashion companies become trend setters.
Aggregating global fashion trend and sales information from a wide variety of sources –including retail sites, social media, designer runway reports, and blogs–Competitive Intelligence (CI) is synthesized from the data, accessible in real time and can be customized to spotlight information relating to the unique priorities or focus of the company.
You can aptly use the term “Trend forecasting” that Wall Street Journal contributor Kathy Gordon used to describe information analysis using Big Data. Leading in this field is the Editd, an apparel data warehouse aimed at helping the world’s apparel retailers, brands, and suppliers deliver the right products at the right price and the right time.
Solutions for a distinct fashion problem
Agile retail companies are using Big Data analytics to identify consumer trends, utilize highly efficient production and distribution systems, and only sell online. The result is products that people want, at prices they can afford, without having to go to a mall.
So why should the fashion houses and e-retailers care about the immense valuable data available through data analytics? A look below will answer your question:
Curbing waste
One constant issue faced by the designers is guessing the right volume of items to be sold. An incorrect value will result in excess items being produced, which will have to be sold at discounted rates to make up for the loss. Using Big Data analytics, you can determine the demand and supply ratio accordingly, and produce in appropriate quantities.
Mass Productions
Customers now want quick service with instant gratification. Mass production is a guaranteed way of satisfying the huge demand. But, it can also backfire with items being produced which may or may not be consumed. Using Big data analytics, retailers can manufacture items based on which products are working and quickly alter the production accordingly.
Aggregation
Instead of pulling solely from internal datasets, companies today are able to pull from a variety of datasets across the web to determine not only what their customers want but also what their competitor’s competition wants. Social media shares, likes, tweets are used to analyze the trends and people’s response to any new design launched by the designers.
Through the use of big data from data collection tools, even the notoriously fickle and creatively driven industries like fashion can more efficiently deliver the products and services that meet consumer demands. Identifying designer influence allows producers, retailers and consumers to make more informed decisions about what they buy, as well as identify tomorrow’s influencers within the industry.
If this article gets you piqued about Big Data and its immense value in transforming your business, do call us at +91-80-4110-5555 or mail to info@sysfore.com.
