Retailers are increasingly combining physical brick and mortar operations with ecommerce capabilities to better address consumer demand for online purchasing. By combining data from physical and eCommerce sites, retailers can extract a variety of outputs using big data analytics that help guide leadership teams in making effective decisions. While big data is a frequently cited term these days, people often struggle to develop an understanding for what it means in practice or how it translates to measurable business value.
Implementing Big Data Projects
The retail sector provides an enlightening context in this regard as it combines the availability and access to underlying data with the ability to map derived insights to tangible business actions. Specifically, the relevant data that retailers can use to derive predictions can come from internal and external sources. Internal historical information might include purchase trends from prior holidays as well as browsing data from ecommerce software. These data sources allow algorithms to map previous behavior to the future using models that also account for changes in traffic volume and customer segments. However, historical data doesn’t provide insights into new trends or product demand.
The Value of Predictive Analytics for Ecommerce
To address this gap, retailers can incorporate external data such as social media content to identify emerging interest for specific products. For example, a surge in conversations around a specific video game or electronic device may indicate latent demand which will translate into gift purchases for the holidays. Together, the data sources comprise a variety of formats and volumes which create a strong foundation for developing a big data application. In order to capture the market potential, organizations must be able to meet the seasonal demand for products through corresponding inventory and capacity to deliver on purchases.
The Benefits of Cloud Based Implementations
The adoption of cloud technologies enables significantly faster time to market for implementations. The alternative approach of building on dedicated, bare metal hardware introduces significant delays due to the time needed to provision hardware and configure systems. Cloud based infrastructure management allows for automation of basic maintenance operations including applying security updates and performing monitoring.
When considering tradeoffs between private versus public cloud options, there are a variety of concerns that come into play. First of all, there are often TCO benefits of a private environment for big data use cases due to the sheer volume of data. Another advantage of private clouds in the context of ecommerce is that they alleviate any potential business risk from storing data on a competitor’s infrastructure. A key benefit of Stratoscale is that it supports using the same tools and APIs from earlier, thereby allowing for a seamless transition between public and private cloud environments.
In order to ensure a positive return on investment when considering IT or software development initiatives, it is imperative that they are scoped with clear business goals in mind. There is also a greater need to intelligently manage inventory and business operations to effectively grow revenue and margins. In conclusion:
Big data and analytics using Hadoop can help drive value for ecommerce businesses by helping to predict consumer demand
Cloud technologies simplify the big data implementation by reducing the time-to-market and addressing complexities related to deployment, provisioning, and maintenance
A Stratoscale based private cloud allows developers and IT administrators to use tools and APIs they’re already familiar with from AWS
Stratoscale can deliver a wide variety of big data projects across different industries. To learn more, visit www.stratoscale.com