1 Big Data and Business Intelligence Integration into Walmart Mario DeSean Booker Big Data and Business Intelligence Integration into Walmart 2 The field of big data analytics and business intelligence represents an interdisciplinary focus within the IT field. These two fields work to build a bridge from the needs of information to insightful business decision methods, and if used properly, can encourage business decisionmakers to drive up revenue, increase market share, establish a competitive edge, and advance the mission and vision statement of the business. Llave (2017) affirmed that Business Intelligence “(BI) is a set of methodologies, processes, architectures, and technologies that transform the raw data into meaningful and useful information which allows users to make informed business decisions with real-time data.” Within the realm of business management, organizations yearn for applications and processes that are designed to process vast amounts of information and provide keen insights. This is necessary to observe and record various forms of activity and performance initiatives to respond to trends within their environment better. Data analytics accompanied by decisionmaking applications aid businesses and management in making well-informed corporate policies. Utilization of business intelligence not only improves business processes, but also allows the business has to have a more holistic understanding of its operations. Further, BI allows them to compete within the market segment. Business intelligence with big data integration provides a business focus which results in keen awareness into various forecast measures. Business intelligence offers an inherent value derived from the utilization of management processes that align with operational procedures; Thus, BI reduces organizational costs and drives up revenue. The business value added by BI must be recognized to capture the benefits associated with big data integration. Many retail businesses have begun incorporating Big Data analytic tools and software to gain business intelligent insight. The integration has been quite beneficial to various businesses within the retail market, most notably Walmart. Big Data and Business Intelligence Integration into Walmart 3 Walmart is, without question, the largest retailer in the Modern Age. The company represents a massive marketplace for consumers. Based on sheer volume of sales, Walmart capitalized on an opportunity to take all of the Big Data contained within the data silos within the data warehouses in Walmart systems and convert that data into insightful information for corporate executives and management so they can align the business (and re-align) to realize its potential. Walmart, like many retailers, desires to traverse the dynamic market conditions within the retail market segments. Walmart underwent Big Data integration in hopes to gain intuitive information to understand how to maximize their profit margins further while simultaneously minimizing costs across the board. The integrated business intelligence and data analytic tools within Walmart provided many benefits, but presented some constraints. Overall, the integration was a success and Walmart still employs business intelligence tools. Walmart Business Review Walmart being one of the largest retailers approached the integration of big data analytics and business intelligence with the mindset of reduction. Reduction of management and leadership at Walmart reduced wage costs. Additionally, Walmart was concerned with increasing its revenue and market share and gaining a competitive edge. One of the foremost concerns was its inability to have a holistic view of the organization. Walmart leadership sensed that they needed to envision the progress in factors that affected sales and drove cost. Intuitively, they enlisted the assistance of BI. Singh, Ghutla, Jnr, Mohammad, and Rashid, (2017) advised that, “Walmart Stores, Inc., try to maximize the profit by providing maximum customer satisfaction in all geographical locations to maintain the standards of the stores.” A common issue is the dynamic market within the retail industry. The market is prone to spikes, peaks, and valleys. Companies Big Data and Business Intelligence Integration into Walmart 4 that are ill-prepared to traverse this narrow market suffer great losses. So, with business intelligence in mind, Walmart sought redress for allocation of resources: inventory, staff, improved supply chain management, and enhanced inventory management. Big Data and Business Intelligence Framework Approaching BI intelligence integration Walmart realized that change was imperative to gain the benefits of this integration. “BI investment that improves demand forecasting will not deliver business value unless the forecasts are actually incorporated into operational business processes that then deliver reduced inventory, reduced order expediting costs, or some other tangible economic benefit” (Loshin, 2003). Overhaul of business practices was one of the key aspects that Walmart got right. The integration of BI and data analytics allowed them to as Islam (2018) stated, gain “visibility into all spending related to analytics and reporting. … leverage this approach to mitigate risks, by better managing credit exposure, creating supply chain flexibility to optimize inventories, and to reduce losses from diversion, counterfeits, revenue leakage, and fraud.” This case study took the datasets from the Walmart sales data warehouse silos and performed relationship analysis. The data sets collected from Walmart’s data warehouse were all contained within CSV files. The data was stored with “Apache Spark with a build version of Hadoop” (Singh, Ghutla, Jnr, et al., 2017). To handling the batch processing as well as stream, Apache Spark was used. Additionally, the sales data expanded three years’ worth of data; contained within those data sets were weekly sales reports as well as expenditure reports that highlighted areas such as wages, fuel costs, and weather reports. These various other aspects were reviewed in an attempt to outline patterns that will cause disruptions in there supply chain or store performance. The analysis of the data was completed using a variety of libraries with Apache Big Data and Business Intelligence Integration into Walmart 5 Spark, including Spark SQL, Spark Streaming, MLib, and Graphx. Moreover, as Singh, Ghutla, Jnr, et al., (2017) informed, “we have used Big Data Technology: MapReduce with Hadoop, Apache Spark combined big data fundamentals in high level API’s for Scala, Python and Java to analyze this tremendous Weekly Sales dataset and outline a pattern and meaning to it…Finally, we used Sparks with its python API, (Pandas – python library for graphing) for graphical visualization.” Benefits and constraints The case study was not met without any constraints. During the ingestion of the dataset, the most noteworthy constraint appears when processing the dynamic datasets with Apache Spark. While Apache Spark supports various reading files, it was difficult to get the application to read CSV files because this format is not natively supported (Singh, Ghutla, Jnr, et al., 2017). To counter this, an additional software application, i.e., Spark SQL was used. Hadoop MapReduce was a viable solution, but it was noted that this application works best with batch processing. These issues stem from the dynamic mix of data from the heterogeneous environments where they were farmed. The author noted that reduced performance and latency were issues during the analysis, which presented another constraint. Conclusion Big data analytics in combination with business intelligence provides meaningful and insightful aspect to business development and growth. Many businesses could benefit from the implementation of these two technologies. Walmart took its first steps into intelligent business by incorporating these two dynamics into is corporate technological architecture. Throughout the case study, it was noted the various benefits derived from the integration. It has been observed that by streamlining the processes, the alignment of strategic management directive with process changes and change management comprehevie enhancement were observed systemicially Big Data and Business Intelligence Integration into Walmart 6 throughout Wal-Mart. Furthermore, the benefits improved production costs in the areas of supply chain and inventory management as well as the perceived growth from understanding customer behavior. However, the author did observe constraints within the actual business intelligence ingestion process. Walmart adapted and did not allow the constraints to hold them back. Many retailers can benefit from this example and move forward to more comprehensive and intelligent business practices. Big Data and Business Intelligence Integration into Walmart 7 References Gangadharan, G.D., & Swami, S.N. (2004). Business intelligence systems: design and implementation strategies. 26th International Conference on Information Technology Interfaces, 2004., 139-144 Vol.1. Islam, N. (2018). Business Intelligence and Analytics for Operational Efficiency. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3163429 Llave, M. R. (2017). Business intelligence and analytics in small and medium-sized enterprises: a systematic literature review. Procedia Computer Science, 121, 194–205. https://doi.org/10.1016/j.procs.2017.11.027 Loshin, D. (2003). The value of business intelligence. Business Intelligence, 11–25. https://doi.org/10.1016/b978-155860916-7/50003-8 Singh, M., Ghutla, B., Jnr, R. L., Mohammed, A. F. S., & Rashid, M. A. (2017). Walmart’s sales data analysis - a big data analytics perspective. 2017 4th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE). https://doi.org/10.1109/apwconcse.2017.00028
