Data management refers to administrative process which includes acquire, validation, storage, protection and processing of the required data in order to ensure about the reliability, accessibility and timeliness of data for the users. For every business organisations, keeping data management software is very important, as because they create and consume data at very unprecedented rate. This study report is based on demonstrating the understanding of broad concepts of data management and data analytics being used in organisation. The study report focuses on how this concept brings changes in the decision making process of the organisation.
Tesco is a British multinational general merchandise and groceries retailer and it’s headquarter is situated in the Welwyn Garden City, England, UK. The organisation was founded by Jack Cohen in the year 1919 as a group of markets in the Hackney, London. At present, they are operating their shops in 12 countries under various or different brands. Around 500000 people are employed by Tesco organisation in 7599 stores across the world including franchise Abuqabita, Al-Omoush & Alwidian (2019).
Tesco is chosen for the study report based on Data analytics and data management as because the organisation makes use of up-to-date data and real time analytics. It is also leading the ways in the field of technology and big data and the achievements of the organisation are not restrained in data accumulation and decipher. The typical business of the Tesco is to deal in general merchandise products as well as in grocery items. It is considered as the biggest food retailer in UK which becomes avant-garde when pictured about technology and data.
Data analytics technologies and techniques leads to provide a means for analyzing data sets and also take out new information that can provide help to organisation for making informed business decisions Ahmed & et.al., (2017). In simple words, Data Analytics can be defined as the method that extracts raw data by making use of logic and statistical tools.
Business intelligence queries helps in answering the basic questions regarding business performance and operations. Big data analytics is one of the forms of advanced analytics that generally involves complex applications with various elements including statistical algorithms, predictive models and what-if analysis powered by the analytics systems.
Data warehousing refers to the process of collection and managing of the data from varied sources that provides meaningful insights of the business organisation. Data warehouse is generally used for connecting and analyzing the business data from various heterogeneous sources Choi, Wallace & Wang (2018). It is considered as the core of Business Intelligence (BI) system that is built for data analysis and reporting purpose.
Cluster computing refers to the process that is used for sharing computation tasks among multiple computers and those machines or computers forms cluster. This system works on the distributed system having networks. Various types of cluster computing may be used according to the performance optimization, business implementations and architectural preferences like high availability cluster, load balancing cluster and high performance clusters.
Data mining can be defined as the process which is used for extracting the usable data from a large set of raw data. This implies analysing data patterns within large batches of data by making use of one or more software. Data mining process aims at analysing massive amount of data for discovering Business Intelligence (BI) which further help organisations to mitigate risks, solve problems and also to seize new opportunities Ghani & et.al., (2019).
Machine learning refers to an application of Artificial Intelligence (AI) which aims at providing systems the ability for automatically learn and also improve from the experiences without explicit programmes. This focuses on development of the computer programs which can access data and also use it learn from themselves.
In general, there are different types of information sources including primary, secondary and tertiary. This is very important for understanding about every types of information source and it is also important to know which is type is perfect and appropriate for the research study prior to information searching and collection Grover & et.al., (2018). The information for this particular assessment was collected from various different websites available on the Internet because it is more significant source for the latest information.
Data management and data analytics are vital for achieving digital success of the business, but they are also challenging and complex Mishra & Singh (2016). The famous supermarket Tesco faces many challenges and difficulties at initial stage. The difficulties faced by Tesco were in the form of sweeping from the maturing customer behaviour and management of requirement for reduction of food waste and also in compensate with the modern rivals. By using the right method and approach, business intelligence can act as a leading source for the competitive advantage for organisations. Organisations have the opportunity to make use of business analytics for driving digital transformation and to redefine customer experience.
Tesco is considered as the first supermarket chain that began tracking the activities of customers through the loyalty card system and it also successfully managed its transition to online retailing business. The organisation also faced the challenges brought by the latest advancements within the technology i.e. the quest for real time data analytics and Big data. The efficiencies were made possible because of the Internet of Things Oussous & et.al., (2018). There are various difficulties and challenges to be faced by Tesco in the future including reduction of amount of food that goes in the waste at the stores. It includes creating efficiencies in the distribution and logistics chains for keeping down the costs and also to minimize environmental impacts of it. Tesco may also face challenge in facing up the emerging business models that compete with their own. Organisation may also find it difficult for gaining a better understanding about the changing nature of the behaviour of customers.
Tesco has observed that process execution can be predicted through data analytics and are key factors for success, and these processes can be steadily introduced, formulated and also tested out. Generally, such processes cannot be prefabricated solutions rather they are considered as pioneer in nature. Tesco considers implementing big data technology as its multi-channel strategy for acquiring the future trends within their customer retailing behaviour which helps in addressing the demands of the users for making use of physical stores, desktops or mobile devices combined (Big Data At Tesco: Real Time Analytics At The UK Grocery Retail Giant, 2016).
Implementing the new change in the business activities and operations also leads to bring new problems and challenges for the organisation. Tesco faced many obstacles that range from evolving consumer behaviour, need for reducing food waste and to squaring up to new competitions. The answer to all these obstacles lies within cutting-edge, most up-to-date data and real-time analytics Pouyanfar & et.al., (2018. Modelling trends within consumer behaviour throws useful insights about how people shop. It not just shows about how people shop in every store but it also shows how people shop for every product. By making use of clustering and analytics, organisation found out about the way products hung together, they way it were bought and the way products behaved. By making use of this essential knowledge, organisation can pre-order the products in the right manner, and make sure that products are in stock and it also reduces the waste.
Tesco also makes use of sensor data for monitoring the temperature of freezers and fridges across the network of different stores. Each and every machine is monitored from central and predictive algorithms are made use of for the purpose of determining when the particular unit will require servicing. There are almost 3500 stores of Tesco within UK only and every store stocks an average of 40000 products and tracking them all in just once involves many challenges and requires creation of more than 100 million data points Rajaraman (2016). This problem can be solved by Big data analytics by deploying analytics technology in which data can be stored instead of moving the data in different batches for the external analytics.
Tesco is preparing to move from data warehousing to data lake model which is based on the Hadoop framework. This framework will be cloud-based repository and centralised for all the data and codified in a manner that makes it usable and accessible by any arm of the organisation as and when it is required Simsek & et.al., (2019). The business of Tesco is rapidly becoming more involved in the open source development. The engineers, developers and data scientists of Tesco are encouraged for making use of open source technology wherever it is possible and for giving back to OS community.
Information and data, within any business organisation, are increasing at an exponential rate which may be generated through sensors, social media, smart phone, connected devices and various other sources. Many organisations focus on looking for adapting the potential of fast-moving, convoluted and enormous streams of the data for attaining the turnaround enhancement in the success and achievement.
The essence areas of operation and research in which Tesco makes use of the data analytics at its forefront is for the anticipation of sales Zhu & et.al., (2018). Data modelling of the consumer’s data provides some important interference regarding their buying behaviours. With the application of model clustering and data analytics, Tesco can find out about the way products are purchased together and the way products behave. Clustering method is implemented by Tesco for ensuring that products are anticipated and they also act in proper way, when the items needs to be ordered so that they remain in stock and also helps in reduction of waste.
Tesco makes use of Github code for supporting the research team, and keeps use of prominence technological augmentation Zhang (2019). The organisation hopes for maintaining market value against more technological- driven and agile initiatives. By effective utilization of the fascinating real-time technology and big data technology and technical system of Tesco as in the globally networked stores and distribution infrastructure, Tesco can effectively bring about great possibilities of success and achievements.
From the analysis, it is learned that business organisations cannot effectively manage the large volume of unstructured and structured data by making use of the conventional and relational database management systems. In order to properly store, access and to process the large datasets in rapid and effective manner, they need to switch from relational data base to Big data analytics and management. Business organisations have various options to choose from wide range of database management systems and several tools.
Big data analytics enables organisation for collecting real-time data from both internal and external sources. Business organisations can make use of big data or data analytic tools for collecting both structured and unstructured data from various different sources. These tools enable organisation for storing, processing and analysing the data in effective manner. But the organisation need to focus on keeping the big data lifecycle fully secured so that they can retain consumers, avoid legal hassle and avoid leakage of personal data.
Therefore, it is recommended that Tesco needs to also implement robust security strategy for collection, storing, analysing, managing and utilizing big volume of data so that they can effectively eliminate the risk related with data exposures and data breaches. Tesco also needs to keep the big data security strategies dynamic and flexible enough so that they can effectively address any new privacy and security issues which may being get generated because of the constant expand within the data volume.
Books and Journal
Abuqabita, Al-Omoush & Alwidian (2019). A Comparative Study on Big Data Analytics Frameworks, Data Resources and Challenges. Modern Applied Science. 13(7).
Ahmed & et.al., (2017). The role of big data analytics in Internet of Things. Computer Networks. 129. 459-471.
Choi, Wallace & Wang (2018). Big data analytics in operations management. Production and Operations Management. 27(10). 1868-1883.
Ghani & et.al., (2019). Social media big data analytics: A survey. Computers in Human Behavior. 101. 417-428.
Grover & et.al., (2018). Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems. 35(2). 388-423.
Mishra & Singh (2016, April). Big data analytics for security and privacy challenges. In 2016 International Conference on Computing, Communication and Automation (ICCCA) (pp. 50-53). IEEE.
Oussous & et.al., (2018). Big Data technologies: A survey. Journal of King Saud University-Computer and Information Sciences. 30(4). 431-448.
Pouyanfar & et.al., (2018). Multimedia big data analytics: A survey. ACM Computing Surveys (CSUR). 51(1). 1-34.
Rajaraman (2016). Big data analytics. Resonance, 21(8), 695-716.
Simsek & et.al., (2019). New ways of seeing big data.
Zhang (2019). Big data security and privacy protection. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 3(2), 35-41.
Zhu & et.al., (2018). Big data analytics in intelligent transportation systems: A survey. IEEE Transactions on Intelligent Transportation Systems. 20(1). 383-398.
Big Data At Tesco: Real Time Analytics At The UK Grocery Retail Giant. 2016. [Online]. Available through: < https://www.forbes.com/sites/bernardmarr/2016/11/17/big-data-at-tesco-real-time-analytics-at-the-uk-grocery-retail-giant/?sh=41965ccc61cf>