7707-GBS Course: Data Analysis Report on BHP Billiton Mining Industry

This report presents a comprehensive data analysis of BHP Billiton, a leading mining company, focusing on the application of Business Intelligence (BI) to optimize cost reduction strategies. The report begins with an executive summary and introduction, providing background on BHP Billiton and the importance of BI in the mining industry, particularly emphasizing the role of data warehouses and data mining. It evaluates BHP Billiton's current BI capabilities, including organizational memory, information integration, reporting and analysis, and information visualization. The discussion and analysis section delves into the company's operational performance, production data, and financial metrics, supported by various figures and charts. The report concludes with recommendations for BHP Billiton, emphasizing the development of BI through technologies like data warehouses, establishing central databases, and creating analytic tools. The report highlights the benefits of BI in improving safety, increasing production, and reducing costs, ultimately advocating for the adoption of innovative technologies and sustainable development practices to enhance the company's performance.

Running Head: DATA ANALYSIS 0
Data Analysis
Report
Student name

DATA ANALYSIS 1
Executive summary
Business intelligence is requiring for betterment in the business processes and operations
of an organization. It provides help to improve business processes as well as growth of
organization. This report will provide introduction and background of the organization.
Mining industry is having daily data of production and other things for managing
different processes of organization. It is also requires different things for decision making for
mining, such as weather conditions.
Many things that make mining industry better, such as business intelligence,
technologies, and many others. Business intelligence is providing a way to reduce cost and
increase profit of an organization. Data warehouse are backbone of the organization in present
era.
BHP Billiton is a brand in the field of mining in Australia. It was world Largent mining
company in 2017. In mining industry, data is gathered from different equipment and sensors.
That data is a key to better decision making for mining. This data is process through different
processes and turn it into intelligence.
This report will provide different strategies for mining through business intelligence and
it will provide help in cost reduction. This report concludes with different recommendations,
which are based on the business intelligence capabilities. Those recommendations are focus on
cost reduction strategies.

DATA ANALYSIS 2
Table of Contents
Executive summary.........................................................................................................................1
Introduction and background...........................................................................................................3
Evaluation........................................................................................................................................3
Organizational Memory:..............................................................................................................4
Information Integration and transformation:................................................................................6
Reporting and analysis:................................................................................................................6
Visualization of information:.......................................................................................................7
Discussion and analysis...................................................................................................................7
Conclusions and recommendations...............................................................................................12
Recommendations for BHP Billiton:.........................................................................................13
References......................................................................................................................................15

DATA ANALYSIS 3
Introduction and background
BHP Billiton is a well-known company in the world, as it is largest company in the field
of mining, petroleum and metals. Business Intelligence (referred as BI) is useful for different
processes of organization for their betterment. Data warehouse is a source of data analytics that
provide benefits for company (Chen, Chiang, & Storey, 2012).
This report is based on BI and it will provide different methods of cost reduction. BHP
Billiton is a huge company and there are many processes for managing different works. It is a
mining company, which is providing business to other industries as well.
Business intelligence is requires for most of companies that are having data from
different sources. Mining companies are based on the data analytics. Therefore, it requires
different softwares and applications for data collection as well as processing (Isik, , Jones, &
Sidorova, 2013).
BHP Billiton was founded in the 1985. It is situated at broken hill in New South Wales. It
is third-largest company in Melbourne by revenue. The Broken Hill Proprietary Company
Limited (BHP) operating the lead and silver mine (bhp.com, 2019).
BHP Billiton has mining operations in Australia, and petroleum operations in Tobago,
Algeria, US, UK and Trinidad. It has coal, copper, petroleum and iron ore operational units with
a development potash project.
BHP Billiton is having more than 62,000 employees and contractors for different
business processes. Headquarter of BHP is situated in Melbourne, Australia. All the huge
operations are controlling from headquarter. It is a dual listed company structure with two parent
companies, which are BHP Group Plc. and BHP Group Limited. It is running by a management
and unified board (BHP, 2019).
This report will provide details of data warehouse uses in different processes of BHP
Billiton, such as management, processing, and other things.

DATA ANALYSIS 4
Evaluation
BHP Billiton is increasing their day-by-day in various fields especially in mining field.
There few things to focus that are business intelligence through technologies by BHP. Data
warehouse and data mining techniques are beneficial for different business processes of BHP
Billiton (bhp.com, 2019).
BHP Billiton is having many data about the mining as well as weather reports. They are
taking helps from other government and private sectors for data and information for their
business. Mining field is requiring a database and data warehouse for different processes of their
business as well as operations. Mining industry is based on two things, which are data and
technology for mining.
(Priebe, Torsten, & Pernul, 2003)
Above diagram is describing about four capabilities of business intelligence, which are
organizational memory, information integration, insight creation and presentation (Sabherwal &
Becerra-Fernandez, 2012).
Organizational Memory:
It is depend on the organization data collection. Every company is having many data
about different processes as well as employees. There are two types of data is stored in the
system that is structures and unstructured data (Ngai, Xiu, & Chau, 2009). Structured data is
gathered from mine planning, processing of plants, and many others. Unstructured data is

DATA ANALYSIS 5
gathered from emails, weather monitoring, and others. Both structured and unstructured data are
useful for system processes (Berkhin, 2006).
In below diagram, train management system is explained, which is used by the BHP
Billiton for transportation.
Source: (Dickerson, 2018)
All the data is stored in the data warehouse and it is used for the Train control system as
well as business systems (Berry & Linoff, 2009). Data warehouse system is providing help to all
the business processes to manage them properly ( Brown, 2012).
Source: (Chowdhury, 2014)

DATA ANALYSIS 6
Data is collected form different processes such as billing, human resources, payroll, ERP,
product, sensors, orders, and many others. All the data is transformed to data warehouse, which
is extracted from different sources ( Creagh, 2018). Online Analytical Processing (OLTP) is
providing different report formatted for marketing, sales and purchases. These reports are
beneficial for decision-making (Linoff & Berry, 2011).
Information Integration and transformation:
Information is processed data through different methods that are useful for decision-
making. BHP Billiton is having different systems for many business processes. As an example,
weather monitoring system is providing many data on daily basis. Therefore, that data can be
used for the different business processes as well as mining processes ( Linden, 2015).
Internet of Things (IoT) can be used for the integrations of data from different sources,
such as sensors, monitors and many other devices. Data warehouse is collecting information
from reliable sources. Therefore, IoT provides better automation and decision making using data
warehouse.
Reporting and analysis:
First two sections are providing raw material for decision-making. Insight creation is
third capabilities that provide better data for effective decision-making. Insight creation uses
functional analytics for identify cause of issues then analysis them. After analysis, make
predictions for future outcomes.
Analytics provide real data about the production and legging with issues of machine or
labor. It provides benefits to different processes as well as cost reduction. Monitoring of weather
condition is beneficial for mining processes of different plants. It reduce cost, as bad weather
conditions are affecting the working as well ( Porritt , 2011).
Business intelligence is helpful for reporting and decision-making for new and old plants
workings. It is helpful for demand and supply operations. It provides data about the demands of
customers (Obeidat, North, Richardson, & Rattanak, 2015).

DATA ANALYSIS 7
Based on the data, managers can promise for delivery of products as per given time. It
provides real time data. Therefore, it is beneficial for the company as well as consumers. BHP
Billiton is providing different services to their consumers (Laney, 2012).
Visualization of information:
Data presentation is a good skill of BI and it will provide benefits to different processes.
Many processes are required previous data and real time data for next decision. BI system is
providing both the data to system as well as managers. It provides maximum benefit and
customizable input for different processes (Larose & Larose, 2014).
Different software applications are provide better visualization for decision-making. They
also provide data in fast way. Those reports are based on the millions of records that are stored in
the data warehouse (Liao, Chu, & Hsiao, 2012).
Discussion and analysis
BHP Billiton is a huge company in the field of mining as well as Australia. It provides
many benefits to their vendors as well as country. They produce a huge amount of coal, iron and
petroleum in Australia as well as different countries (Mentz, Jooste, & Van Biljon, 2014).
Source: (BHP, 2019)
Data mining is providing many advantages to the BHP Billiton. Few of them are
improving safety, increasing production, and reducing cost (Crozier, 2017).

DATA ANALYSIS 8
BHP Billiton is producing the entire mineral from different site at worldwide level. There
productions are showing in below diagram.
Source: (BHP, 2019)
In below diagram, operational performance of BHP Billiton is showing. It shows
production for Dec 2018 half year and guidance for the 2019 financial year in summarized
details.
Source: (BHP, 2019)
BHP Billiton is increasing prices according to year and different cost of business
processes. Below figure is showing the average realized prices achieved for major commodities
of BHP Billiton (VANTAZ, 2014).

DATA ANALYSIS 9
Source: (BHP, 2019)
Below chart is showing BHP Billiton part in mining field and other companies in
percentage.
Source: (BHP, 2019)
Below figure is showing the changes in the production of BHP Billiton between 2016 and
2017.

DATA ANALYSIS 10
Source: (TheValuePortfolio, 2018)
Below figure is showing the data about the BHP Billiton ltd. Shares market status from
2015 to 2018. It goes down in the 2016 because of natural disasters.
Source: (BHP, 2019)
Below figure is showing BHP Billiton estimated earning of years 2018, 2019 and 2020.

DATA ANALYSIS 11
Source: (Gilroy, 2018)
BHP Billiton is makes changes in their working and it adopts different processes that are
better for sustainable development. BHP is fully supported of sustainable development. They are
using renewable energy sources for different processes. Below diagram is showing a flow
infrastructure for fulfill the sustainable development goals (Shmueli, Bruce, Yahav, Patel, &
Lichtendahl Jr., 2017).
Sources: (BHP, 2019)

DATA ANALYSIS 12
Sustainable development is also based on the business intelligence. However,
technologies are providing different things to modified processes that are reduce cost of
company. In addition, BHP Billiton is using best technologies for sustainable development
(Vercellis, 2011).
Conclusions and recommendations
It is concluded that form the basis of above sections of this report that, business
intelligence is play a key role for growth of an organization. BHP Billiton is uses technologies
and business intelligence for their business process and they got success in their field. They are
always working in the field of mining with technologies and business intelligence.
Technological changes are must for any business, such as BHP Billiton is applied in their
mining processes. They also support sustainability goals and they created different activities for
sustainable development. Data warehouse are providing better data analytics for decision-
making.
Innovations are beneficial for the growth of organizations. BHP Billiton is having their
own research and development team at different places for disruptive innovations. This report
evaluates different things with the help of business intelligence. BI is beneficial for decision-
making that will reduce cost of different operations.
New IT-services and operations technologies provide new advantages to the company in
terms of revenue and growth. It is a way to merge both services and use them for better results. It
provides better growth and it reduces the cost.
Data mining provides data for mining as well as for business. Therefore, one technology
provides different advantages to the organization. It will also make changes in business processes
that are based on the statistics.
Data warehousing is providing growth in different terms. Innovations are useful for
different processes of the BHP Billiton. IoT can make it better through sensors and different
application. Finally, it is included that business intelligence is beneficial the organizations and it
provides an exponential growth in their business.

DATA ANALYSIS 13
Recommendations for BHP Billiton:
Business intelligence is playing an important role in mining companies for sustainable cost
management. Business intelligence is having different capabilities, such as data warehouse. It
uses internal data sources for cost reduction. BHP Billiton must follow these recommendations
for growth of company in future.
1. Develop business intelligence through technologies, such as data warehouse and mining
2. Establish central databases for providing real time information to business systems.
3. Create analytic tools with the help of business intelligence and use them for cost
reduction strategy.
4. Many vendors are providing tools for such types of facilities, such as oracle, IBM and
many others.
5. BI is an agile approach to sustainable development and it provides better decision-making
skills to managers for different processes that are based on the data and information of
internal and external sources.
6. Develop different domains for collection of data that is used for decision-making of other
sites.
7. Introduced business intelligence system in organization for managing different operations
8. Develop cost reducing strategies for increasing benefits through business intelligence
9. Data mining techniques can provide benefits for decision-making to BHP Billiton
business processes.
10. Merge operational technologies with new IT technologies for more growth.

DATA ANALYSIS 14
References
Brown, M. (2012, December 11). Data mining techniques. Retrieved from IBM:
https://www.ibm.com/developerworks/library/ba-data-mining-techniques/index.html
Creagh, B. (2018, February 1). The top mining trends of 2018. Retrieved from australianmining:
https://www.australianmining.com.au/news/top-mining-trends-2018/
Linden, A. (2015, July 9). Advancing Business With Advanced Analytics. Retrieved from
www.gartner.com: https://www.gartner.com/doc/3090420/advancing-business-advanced-
analytics
Porritt , K. (2011, January 11). Copper. Retrieved from www.ga.gov.au:
http://www.ga.gov.au/data-pubs/data-and-publications-search/publications/aimr/copper
Berkhin, P. (2006). A survey of clustering data mining techniques. In Grouping multidimensional
data. Berlin: Springer.
Berry, M., & Linoff, G. (2009). Data mining techniques. New Jersy: John Wiley & Sons.
BHP. (2019, January 28). About us. Retrieved from bhp:
https://www.bhp.com/our-approach/our-company/about-us
bhp.com. (2019, February 13). Our approach. Retrieved from www.bhp.com:
https://www.bhp.com/community/our-approach
Chen, H., Chiang, R., & Storey, V. (2012). Business intelligence and analytics: from big data to
big impact. London: MIS quarterly.
Chowdhury, S. (2014, May 27). Big data and data warehouse augmentation. Retrieved from
IBM: https://www.ibm.com/developerworks/library/ba-augment-data-warehouse1/
index.html
Crozier, R. (2017, January 17). BHP Billiton to double permanent IT workforce. Retrieved from
www.itnews.com.au: https://www.itnews.com.au/news/bhp-billiton-to-double-
permanent-it-workforce-448438

DATA ANALYSIS 15
Dickerson, G. (2018, april 5). AusRAIL PLUS 2005 Presented by:. Retrieved from
/slideplayer.com: https://slideplayer.com/slide/13070373/
Gilroy, A. (2018, December 27). Why Are Analysts Projecting Falling Earnings for BHP
Billiton? Retrieved from marketrealist.com: https://marketrealist.com/2018/12/why-are-
analysts-projecting-falling-earnings-for-bhp-billiton
Isik, , O., Jones, M. C., & Sidorova, A. (2013). Business intelligence success: The roles of BI
capabilities and decision environments. Information & Management, 50(1), 13-23.
Laney, D. (2012, February 1). Ten Reasons to Reach Beyond Basic Business Intelligence.
Retrieved from www.gartner.com: https://www.gartner.com/doc/1911314/reasons-reach-
basic-business-intelligence
Larose, D. T., & Larose, C. (2014). Discovering knowledge in data: an introduction to data
mining. New Jersy: John Wiley & Sons.
Liao, S.-H., Chu, P. H., & Hsiao, P. Y. (2012). Data mining techniques and applications–A
decade review from 2000 to 2011. Expert systems with applications, 39(12), 11303-
11311.
Linoff, G., & Berry, M. (2011). Data mining techniques: for marketing, sales, and customer
relationship management. New Jersy: John Wiley & Sons.
Mentz, J., Jooste, C., & Van Biljon, J. (2014). Usability evaluation for Business Intelligence
applications: a user support perspective . South African Computer Journal, 32-44.
Ngai, E., Xiu, L., & Chau, D. (2009). Application of data mining techniques in customer
relationship management: A literature review and classification. Expert systems with
applications, 36(2), 2592-2602.
Obeidat, M., North, M., Richardson, R., & Rattanak, I. (2015). Business intelligence technology,
applications, and trends. International Management Review, 11(2), 47-56.
Priebe, Torsten, & Pernul, G. (2003). Towards integrative enterprise knowledge portals. In
Proceedings of the twelfth international conference on Information and knowledge

DATA ANALYSIS 16
management . (pp. 216-223). ACM.
Sabherwal, R., & Becerra-Fernandez, I. (2012). Business Intelligence: Practices, Technologies
and Management. John Wiley & Sons, Inc.
Shmueli, G., Bruce, P., Yahav, I., Patel, N., & Lichtendahl Jr., K. (2017). Data mining for
business analytics: concepts, techniques, and applications in R. New Jersy: John Wiley
& Sons.
TheValuePortfolio. (2018, January 8). BHP Billiton - Enormous Mining Company With Strong
Assets. Retrieved from seekingalpha.com: https://seekingalpha.com/article/4135881-bhp-
billiton-enormous-mining-company-strong-assets
VANTAZ. (2014, Auguest 14). Big Data Analytics : the Hottest Disruptive Technology in
Mining Right Now? Retrieved from vantaz.com: https://vantaz.com/big-data-analytics-
hottest-disruptive-technology-mining-right-now/
Vercellis, C. (2011). Business intelligence: data mining and optimization for decision making.
New Jersy: John Wiley & Sons.