Microsoft Power BI Research Articles

B-149 Next-generation Sequencing Via Targeted Metagenomics for Broad Antimicrobial Resistance Surveillance

Abstract Background Antimicrobial-resistant infections secondary to the overuse of antibiotics are a major public health threat. The standard of care for identifying resistance is antimicrobial susceptibility testing, the phenotypic characterization of minimum inhibitory concentrations (mic) for antibiotics in the presence of bacterial growth, but these methods are labor intensive, have long turnaround times, and face challenges with non-cultivable bacteria. Molecular methods for antimicrobial resistance (AMR) ascertainment are high-throughput, robust, and sensitive and have gained interest as a genotypic complement to traditional phenotypic methods. Since the COVID-19 pandemic, next-generation sequencing has emerged as the leading technology for tracking and surveillance of infectious diseases and antimicrobial resistance, emphasizing the need for flexible sequencing panels that are easily interchangeable and capable of detecting pathogens and AMR genes. Methods In a collaboration between Illumina, a national retail pharmacy, and Aegis Sciences Corporation, residual, self-collected nasal swab samples (n = 4390) submitted for COVID-19 testing from patients across the U.S. were sequenced using the Respiratory Pathogen ID/AMR Panel (RPIP, Illumina – For Research Use Only), a target capture-based next-generation sequencing panel targeting 282 respiratory pathogens and 2097 relevant AMR markers. Sequencing data was analyzed using the Explify RPIP Analysis app (BaseSpace, Illumina) and paired with self-reported patient data submitted via an online questionnaire. Data including pathogens and anti-microbial resistance (AMR) genes detected, age, race, gender, residing state of the patient, collection month, self-reported symptoms, and health risks were collated, imported into Microsoft PowerBI software, and used to create interactive visuals for a surveillance dashboard. Results In this cohort of sequenced specimens, 85.1% (n = 3576) had one or more viral, bacterial, or fungal pathogens present, 41% (n = 1816) had one or more AMR genes present, and 38.4% (n = 1685) had one or more pathogens and AMR genes co-detected. Twenty-six different AMR genes were identified with the most prevalent being Erm 23S ribosomal RNA methyltransferase (65.5%; n = 1115). Erm was identified in samples from all 50 US states and was co-detected with staphylococcus aureus (18.2%; n = 216) and streptococcus pneumoniae (4.9%; n = 57), among others. Following Erm in prevalence, this cohort of samples harbored genes for trimethoprim resistant dihydrofolate reductase (dfr = 27.9%), tetracycline-resistant ribosomal protection protein (tet = 21.0%), and macrolide phosphotransferase (MPH = 14.2%). The data also revealed AMR gene-pathogen co-detections listed as CDC serious threats, such as the mecA gene responsible for methicillin resistance in staphylococcal species. The mecA gene was co-detected in 5.3% (n = 28) of staphylococcus aureus positive samples in this cohort. Finally, although not classified as a serious threat, neuraminidase inhibitor resistance, associated with less susceptibility to anti-virals, was found in 12% (n = 15) of all influenza A (H3N2) infected samples (n = 112). Conclusions Completion of these studies demonstrated that next-generation sequencing using targeted metagenomics with RPIP is a cost effective, high-throughput option for large-scale surveillance of AMR genes in potential respiratory infections.

A health integrated platform for pharmacy clinical intervention data management and intelligent visual analytics and reporting

ObjectiveOur initiative aimed to improve the system used to capture pharmacist clinical interventions to better support staff to document, manage and identify trends in medication-related problems (MRPs). The aim of the study was to develop an electronic tool which is easily accessible by most electronic devices with secure data storage and access. MethodsA REDCap® database was designed for documentation of pharmacy clinical interventions. Information documented can be retrieved in real-time and can be integrated to Microsoft Power BI® for real-time data visualisation. The dashboards were customised to display useful information including pharmacy clinical intervention details, common MRPs, common medications involved available to users at real time. ResultsA total of 4343 interventions were documented from July 2022 to March 2023. The most common MRPs were omission of regular medications 876 (20.17%), condition untreated 722(16.62%), and contraindications apparent 451 (10.38%). The most common medications involved include iron 244 (5.62%), enoxaparin 231 (5.32%), macrogol laxatives 208 (4.79%), multivitamin 206 (4.74%), colecalciferol 179(4.12%), tramadol 156 (3.59%). ConclusionThis study demonstrated the significance of integration of health application tools of REDcap and Power BI in the data management and intelligent visual analytics and reporting.

Implementation of Microsoft Power Bi in Monitoring Product Sales to Maximize Sales Potential and KPI Sales at PT UPS (PT Unggul Prima Sejati)

This study discusses the implementation of Microsoft Power BI as an effective tool in monitoring product sales and maximizing sales potential. In an increasingly connected and data-driven business era, a deep understanding of sales data and its intelligent use can give companies a competitive advantage. This paper will explain why Microsoft Power BI is the right solution, implementation steps, and its benefits in monitoring product sales and optimizing sales potential.

Use of Microsoft Power BI to display pregnancy related performance statistics within NHS trusts

ObjectiveWe wanted to create a dashboard that allowed midwives and doctors to monitor the performance of their NHS Trust by viewing the statistics relating to their performance in identifying babies at risk due to not growing well in the womb (small for gestational age, SGA), the single largest cause of stillbirths and subject to national guidelines and reporting requirements. Antenatal detection of SGA allows clinicians to undertake further investigations and plan for a timely delivery.
 MethodThe use of Power BI instead of a solution requiring software development allowed the data analysis team to be in control of creating the application and facilitate a streamlined updating process. We used the dashboard feature, dropdowns and radio buttons to display statistics relating to the rate of identification of SGA at antenatal ultrasound scan as a proportion of all babies that are SGA at birth (sensitivity) as well as false positivity. The dashboard is contained within the web-based application to monitor growth during antenatal care. Applying the row level security feature with DAX formula, we were able to personalise the report for each Trust depending on who logged into the web-app.
 ResultsThe application facilitates monitoring performance of the service in real time, longitudinally by month, quarter and year as well benchmark cross-sectionally against network/regional and national averages. The dashboard lets clinicians access their information in a clear and secure manner without the need for a separate link. The ready availability of data allows Trusts to enact policies to improve their performance and ultimately prevent avoidable deaths, and has contributed to the year on year decline in stillbirth rates in units that have been running this application.
 ConclusionDevelopment of this dashboard has resulted trusts being more aware of their own data to promote improvements in antenatal care.

Pengembangan Sistem Business Intelligence Dalam Monitoring Performa Perusahaan Multi Company

Multi-company companies have challenges in managing subsidiary data into performance information of all subsidiaries in one window. This is due to the variation of data dimensions according to the business processes of each subsidiary. CV. XYZ is a holding company engaged in the food & beverage business. CV. XYZ currently manages three companies consisting of restaurants, catering, and tent and decoration rental. The problem faced by the company owner is the limited access to company performance in one information window. Each company has working papers in Excel format to record expenditure and income transactions. This article proposes the development of a website-based business intelligence system to overcome the problems of CV. XYZ. The purpose of developing a business intelligence system in this article is to provide access to the performance of each subsidiary in one website media. The business intelligence system is developed through the stages of data collection and analysis, data warehouse design, ETL process, and data visualization with Microsoft Power BI. The data warehouse design uses Kimball's nine-step method which produces a data warehouse with a star scheme. The developed Business Intelligence system was tested using the UAT method. The UAT test results show that the system development is following the company's needs as indicated by the UAT score of 92%

Rancang Bangun Dashboard Penjualan pada PT. XYZ dengan Microsoft PowerBI

One of the most popular and most widely used technologies among people today is the internet. Starting from studying, shopping, working, doing business, communicating, everything can be accessed only by using the internet or in other words referred to as online activities. People are now trying to expand their business online, one of which is PT. XYZ. This company is a retail company that has an online and offline distribution system and sells power tools and household appliances. This company already has an application-based system. Therefore, the dashboard design for this company will be used to provide a summary of sales for three months from tokopedia, shoppe, lazada and tiktok shop to make it easier for company leaders to make decisions. The data collection method was carried out by interviewing and dashboard design using the prototyping method. This design will produce a dashboard using the Microsoft PowerBI Desktop application which can provide visual information about PT.XYZ's sales data.

Behavioral Welfare Research for the Management of Sanctuary Chimpanzees (Pan troglodytes).

Chimp Haven is a sanctuary for chimpanzees retired from biomedical research, rescued from the pet trade, or re-homed after other organizations could no longer care for them. To provide optimal care for over 300 chimpanzees, Chimp Haven's animal care team includes experts in behavioral science, veterinary treatment, and husbandry practices. To aid these teams in making routine welfare management decisions, a system of behavioral metrics provides objective data to guide decisions and track outcomes. Chimp Haven has built and piloted seven behavioral metric protocols over the past 5 years to provide staff with an objective and comprehensive picture of the chimpanzees' behavioral welfare. The data from behavioral observations, staff surveys, and routine staff documentation are analyzed and processed through Google Forms, ZooMonitor, Microsoft Power Bi, Microsoft Excel, and R. Each metric assists staff in making data-based decisions regarding the management of captive chimpanzees related to abnormal behavior, hair loss, wounding, social relationships, positive reinforcement training and overall wellness. In this article, we explore examples of each metric and how they have been utilized to monitor and make decisions for both social groups of chimpanzees as well as individuals. These metrics can be collected and shared easily in an understandable format, which may provide an important framework for others to follow to enable the tracking of welfare for other sanctuaries, non-human primates, as well as other species.

Xylooligosaccharides: A Bibliometric Analysis and Current Advances of This Bioactive Food Chemical as a Potential Product in Biorefineries' Portfolios.

Xylooligosaccharides (XOS) are nondigestible compounds of great interest for food and pharmaceutical industries due to their beneficial prebiotic, antibacterial, antioxidant, and antitumor properties. The market size of XOS is increasing significantly, which makes its production from lignocellulosic biomass an interesting approach to the valorization of the hemicellulose fraction of biomass, which is currently underused. This review comprehensively discusses XOS production from lignocellulosic biomass, aiming at its application in integrated biorefineries. A bibliometric analysis is carried out highlighting the main players in the field. XOS production yields after different biomass pretreatment methods are critically discussed using Microsoft PowerBI® (2.92.706.0) software, which involves screening important trends for decision-making. Enzymatic hydrolysis and the major XOS purification strategies are also explored. Finally, the integration of XOS production into biorefineries, with special attention to economic and environmental aspects, is assessed, providing important information for the implementation of biorefineries containing XOS in their portfolio.

Tracking emergency response actions during COVID-19 leads to development of an innovative public health evaluation tool

SettingEarly in the pandemic, KFL&A Public Health needed a way to capture, organize, and display COVID-19-related events to be accountable for and evaluate our actions.InterventionWe used accessible software (Microsoft Office 365 suite, Microsoft PowerBI) to develop a data collection and visualization system. The Canadian Institute for Health Information (CIHI) developed a timeline and categorization approach for provincial and national COVID-related interventions, which was used to develop a regional version for local events using similar categories. We collected and displayed qualitative data alongside epidemiological data that allowed users to display different timelines of actions and outcomes and evaluate our response.OutcomesIn developing the timeline, we took stock of the information and data we wanted to collect, sort, and display locally. Next, we collected information on response actions, case and contact tracing, and staffing changes in a database that we displayed on a timeline. We included CIHI’s data set to provide insight into pandemic response across all jurisdictions.ImplicationsOur timeline tool has many advantages for public health authorities beyond responding to a rapidly evolving emergency. By collecting information on events as they occur, decisions and actions are documented that may otherwise be overlooked. This enables decision-makers to visualize the impact of public health actions on health outcomes over time. The tool is completely customizable and scalable depending on the project scope and we plan to apply this method to other public health programming. Finally, we include lessons learned from quickly developing these tools in a real-time pandemic setting, both locally at KFL&A Public Health and nationally at CIHI.

Investigation of Essential Skills for Data Analysts

As the data-analysts job market grows, many colleges and universities have started offering a data analytics curriculum. However, there are potential gaps between the skills business organizations expect of data analysts and the skills universities and colleges teach their students. This study collected 2500+ data-analyst job ads posted on LinkedIn and analyzed them using distribution analysis, cross-tabulation analysis, and cluster analysis. Among many findings, this study identified five most essential nontechnical skills and five most essentials areas of technical skills. In addition, of 90+ computer programs business organizations expect data analysts to use, this study identified SQL, Microsoft Excel, Tableau, Python, and Microsoft Power BI to be the five most essential computer programs for potential data analysts to master.

Business Intelligence for Decision Support System for Replenishment Policy in Mining Industry

The mining industry has unique characteristics in the sense that usually, the plant is located in a remote area while the headquarters are located in an urban area. These conditions pose challenges for the industry related to coordination within companies. This coordination is very important, especially in relation to the decision-making that must be carried out by the company. One of the important managerial decisions is related to the replenishment policy. To make replenishment decisions, companies need past data, such as biodiesel consumption rate, and current data, such as current stock and storage capacity, where the source of those data is in the plant. Often, decisions must be taken quickly because they have impacts on the continuousness of production operations at the plant. However, the remote location and shipping routes across rivers have created new challenges in the flow of goods and services supply because the shipment depends on the tides of the river. This research proposes a business intelligence system that collects, sorts, and visualizes data, then analyzes the replenishment decision to support decision-making in the mining industry. The system uses Microsoft Power BI software which is integrated with the company’s ERP system. To illustrate the applicability of the proposed system, it is applied to a coal mining company, especially in relation to the replenishment policy of biofuel. The result of this study indicates that the proposed system can work. In addition, it can reduce decision-making time by 220.65%.

PERANCANGAN DASHBOARD UNTUK PELAYANAN SIRKULASI DI PERPUSTAKAAN UNIVERSITAS TARUMANAGARA

This journal writing is made with the following objectives, namely to designing the Circulation Services Dashboard at the Universitas Tarumanagara Library using Microsoft Power BI, monitoring the performance evaluation directly from 3 aspects of circulation services at the Universitas Tarumanagara (UNTAR) Library based on key performance indicator (KPI), and make it easier for library managers to read all circulation service transaction data based on the dashboard.
 By using literature study method and requirements prototype method, the dashboard design is displayed in the form of the bar chart using Microsoft Power BI. The design is divided based on 3 aspects, namely adding book titles, adding book copies, and book borrowing transactions.
 Based on the results of testing by the user on the Circulation Services Dashboard at the Universitas Tarumanagara Library, it can be concluded that the dashboard can display Year Filters, Month Filters, Science Field Filters, Book Title Addition Diagrams, Book Copy Addition Diagrams, Book Borrowing Transaction Diagrams, KPI Diagram for Adding Book Titles per Year, KPI Diagram for Adding Book Copies per Year, and KPI Diagram for Book Loan Transactions per Year properly and smoothly according to the user requests.

Cricket Player Analytics using DAX

Cricket is a hugely popular sport, the popularity of the shorter forms of cricket, and particularly T20 cricket, is undoubtedly increasing apparently complicated the process of player selection. Visual Insights of players performance help in find out the best players. Data Analysis Expressions and Data Visualization has the potential to revolutionize the pruning process by creating the insights from huge datasets. The goal of the project is to create dashboards using Data Analysis Expressions and Microsoft power bi to determine the player analytics on website that can be easily available for everyone. The project is divided in to five dashboards. The first module focuses on selecting a team from total players. The second dashboards comprise of entire matches summary that exist in the dataset. The third dashboard provides the players who could have the potential to hold the winning possibilities over 90 percent. The fourth dashboard provides the analytics of every player. The final dashboard generates analytics based on the user requirements.

Addressing Proficiency Gaps in Future Skills Between Employers and Learners Through Data Visualization.

The pandemic has principally changed the way the construction industry operates. It has caused a profound shift in how we conduct our work, with a large-scale take-up of remote working and changes in our digital approach. The way we work is changing. All these impacts challenge the traditional supply chain and working practices of the construction industry negatively, resulting in price escalations, additional costs, loss of revenue, payment delays and increase in disputes and claims. This study aimed to assess the skill proficiency of learners and narrow the employers' and young engineers' perspectives on what are the future skills requirements in the construction industry in the world of digitalization. This study, which comprised two surveys entitled "Future Skills-What does the future look like for young engineers?" (for employers) and "WLA Survey in "Future Skills"-The Proficiency Analyses of Young Engineers-to-be" (for learners), was a part of the Workplace Learning and Assessment (WLA) Engagement Series for students. This research attempts to map skill proficiency of learners (or young engineers-to-be) with the future skill requirements of the employers and to make recommendations on the construction-related institutional arrangements. A quantitative approach by using online surveys as the main data collection tool was adopted. A sample of 20 WLA-participating employers and 23 WLA-participating students in construction companies was generated. In December 2021, the project team initiated two surveys to explore the expectation for the future workforce in the construction industry. Interview results covering various construction-related disciplines, including civil engineering, building studies, surveying and building technology, were analysed and illustrated using Microsoft Power BI. Content analysis with data visualizations was used to identify major themes. This study has shown that employers and students have different perceptions of skills and attributes as critical competencies for a successful workforce. On a positive note, there was a high level of satisfaction for both employers and learners in "Training Structure" and "Training and Development". This study highlighted that students did not have the appropriate level of knowledge as expected by their employers in key subject areas of the construction industry. Employers expressed a clear expectation for the roles and responsibilities of young engineers in their organizations. Areas of practice such as building information modelling (BIM), "Problem Solving", and "Presentation Skills" were highlighted as critical for the future. The competency of youngsters in achieving targeted vision and goals as well as the competency in striving for continual improvement was identified as highly relevant for the future. There was potential for young engineers to play a more active role in their organizations and to repackage their technical skill and interpersonal skill sets for anticipated future roles. The choice of the quantitative research design approach was guided by the need to capture numerical data in the construction industry of Hong Kong for the purpose of illuminating differences in perspectives among participants about future skills for WLA implementation in vocational and professional education and training (VPET). This study can help to investigate the skill proficiency gaps that employers will be looking for and how WLA can bring maximized benefits to students and companies. Based on the results, the students can be better informed about the workplace settings and be prepared for the upcoming industrial attachment or apprenticeship programme with WLA. Feedback provided by the companies can help support students' transition into the world of work. On the other hand, by understanding learners' self-perception, this adaptation made by the companies could result in what looks to be part of a longer-term change in how we work, particularly with a move to increased use of hybrid working. The statistical models with data visualization based on Power BI can also lead to the experimentation and inference that inform the institution's strategy.

Determining the correlation between old age adaptation, aging in place and depression in older adults: A descriptive correlational study

We conducted this study to determine the correlation between old age adaptation, aging in place, and depression in older adults. We carried out the descriptive correlational study with older adults (n:319) Ağrı Provincial Directorate of Health between October 2021 and April 2022. “SPSS 25 and Amos 23 programs” were used in the analysis of the data. Python 3.11.1, Microsoft Power BI programs were used for machine learning and graphical visualizations. In the study, it was determined that the model for the relationship between aging at a place level, adaptation difficulty in older adults level, and geriatric depression level was significant (F(2,316) = 37.002, p = 0.001). The aging in place level and the adaptation difficulty in older adults level explain 18.5% of the total variance of the level of geriatric depression. In the regression model, it was determined that the increase in the level of aging in place (t = −6.081, p < 0.001) and the decrease in the level of adaptation difficulty in older adults (t = 4.107, p < 0.001) of the participants caused a statistical decrease in the level of “Geriatric Depression.” It has been determined that adaptation difficulty in older adults has a moderator role in the relationship between geriatric depression level and aging in place level. In our data set, while the estimate of the presence of depression was 40 % with logistic regression analysis, it was 97 % with Random Forest. The study determined that as the level of aging in -place increased and the adaptation difficulty in older adults decreased, and depression decreased.

Business Intelligence Tools for a Digital Services Company in Peru, 2022

The objective is to propose the use of the business intelligence tool Microsoft Power BI to contribute to the best decision making in the digital services company; there are deficiencies in the ERP integrator system currently used in the company, impairing decision-making in management and corresponding headquarters. The research is of an applied type, considering as a sample those involved in the operation of the ERP integrator system. The analysis of the ERP integrator and business intelligence Power BI software was used, obtaining as results that the use of ERP integrator stores a large magnitude of data that is not easily understandable, complex reading of reports, and lack of statistical graphs. Business intelligence Power BI was applied as a solution tool, obtaining tables designed with complete and correct data, extraction of tables for their subsequent relationship, and understandable statistical graphics; Power BI allows collaborators greater understanding when reading results.

USING A REAL TIME DASHBOARD TO SUPPORT POPULATION HEALTH IN INFLAMMATORY BOWEL DISEASE

Abstract The Phoenix Children’s Hospital (PCH) Inflammatory Bowel Disease (IBD) Clinic provides care for nearly 500 patients. As a group, PCH is part of the ImproveCareNow (ICN) network—a collaboration of over 100 centers worldwide to improve IBD care. Patient care has followed ICN guidelines including a weekly pre-visit planning (PVP) session. PVP is a time intensive process of manual chart review and data gathering for upcoming clinic patients. To improve this process and patient care, our group created a real-time IBD dashboard. OBJECTIVES: The aims of the dashboard were to identify and validate our patient population, improve efficiency by automating data gathering for PVP, and create a visual representation . Secondary aim, was to optimize processes including documentation, order entry and timely follow-up. METHODS: Data is sourced from the Allscripts electronic medical record (EMR). Data retrieval is contingent upon documentation. Our population of patients with IBD was identified based on a charted ICD-10 diagnosis of CD, UC or IC. PCH has a data warehouse of orders, results, Admission-Discharge-Transfer documentation, and flowsheets from the EMR and external data sources. Data is harvested and hosted using Microsoft Power BI for live review at weekly PVP. Once desired data points were hosted, focus was on process improvement (proper documentation, follow-up orders, and patient visits every 200 days). RESULTS: The dashboard hosts patients seen within the last 200 days, provider follow-up order placement, and physician global assessment (PGA) since January 2021. The percent of patients with follow-up orders placed was 61% in 2021. With dashboard enhancements and data visibility, this improved to 99% as of October 17, 2022. Physician global assessment (PGA) was recorded in 81% of encounters in 2021. Our most recent documentation rate is 92% on October 17, 2022. Our group had seen 82% of patients within the 200 days in 2021. Currently we have seen 89% of patients within 200 days as of October 17, 2022 (of these 91% of patients with active disease have been seen). We have instituted a work-flow process with schedulers to ensure patients are contacted and scheduled and not transitioned or moved. Figure 1 Historical Data from 1/2021-10/2021 Figure 2 Current Data as of 10/17/2022 CONCLUSIONS: With time, the IBD dashboard has proven to be a powerful tool in improving process measures. Our hope is these improvements will lend themselves to improved patient outcomes. With the ability to view data in real time in an automated fashion, staff hours have been saved and reallocated to other patient care needs. With continuous review of the data and introduction of accountability, we continue to see improvement. We now have the capacity to add additional metrics to the dashboard and our this can be viewed as a proof of concept for use in other specialties and chronic disease states.

Formulation of Effective Microorganism [EM] to Analyse its Impact on Municipal Wastewater Management

Discharging wastewater from households, industries, and other sources into the environment without treatment hurts the ecosystem as well as people’s quality of life by causing negative impacts on all living species, including health concerns to humans such as diarrhoea which kills 3,50,000 Indian children annually and only 33% of India’s urban wastewater is treated. The majority of energy is dedicated solely to the aeration process, which regulates the degradation of organic matter (sludge) found in wastewater, which is one of the most critical issues in wastewater treatment. As a result, the goal of this research is to develop long-term strategies for degrading organic materials using Effective Microorganisms Technology (EM). EM, also known as Effective Microorganism, is a carefully selected and proportioned liquid culture of fermenting microorganisms. In this study, three microorganisms were isolated from various sources, including soil, yogurt, and milk by serial dilution and spread plate technique, each isolate was made into a pure culture after incubation. They were identified by the VITEK method as Pseudomonas aeruginosa, Lactobacillus sporogenes, and Candida albicans. The microbial consortium was then formed by incubating all three organisms in a nutrient broth that had been modified. Each microorganism culture and formulated microbial culture were added to sewage samples taken in Erlenmeyer flasks. All samples were tested for physico-chemical parameters such as pH, BOD, COD, TDS, TSS, SO4 ²– and Cl- after a three-day incubation period at room temperature. The standard deviation method was used for statistical analysis and Microsoft Power BI was used to visualize the results. Lactobacillus sporogenes was the only culture that showed a significant reduction in all parameters except one when compared to other cultures that showed a reduction in most parameters except a few. As a result, Lactobacillus proved to be effective in wastewater treatment when compared with other cultures. Further research is required to determine its true potential.

Teaching Case: Learning Skills of the Data Analytics Lifecycle with Microsoft Power BI and National Parks Data

Like many organizations, the U.S. National Parks Service has done an excellent job of collecting and storing data for years about variables of interest. However, there are steps beyond the collection and storage of data that must be taken to transform that data into valuable information that can inform strategic business decisions. This teaching case introduces students to the data analytics lifecycle and the various processes for preparing data to make decisions. Students gain a familiarity with the leading data analytics software Microsoft Power BI as well as Microsoft Excel and SQL Server Reporting Services (SSRS) to inform data-driven decisions. This case is relevant to undergraduate and graduate students in information systems and other disciplines prioritizing data analytics. The case was not developed in conjunction with the National Parks Service; the case uses real-world data made publicly available by the National Parks Service but the narrative and questions posed are fictional.

ОСОБЛИВОСТІ АВТОМАТИЗАЦІЇ РОЗРАХУНКІВ ЗАРОБІТНОЇ ПЛАТИ ТА СОЦІАЛЬНИХ ВИПЛАТ НА ПІДПРИЄМСТВІ ЕНЕРГЕТИЧНОЇ СФЕРИ

The energy sector in Ukraine plays a strategic role in ensuring the country's energy security and supporting sustainable economic growth. Changes in this sector can have an impact on the lives of citizens and the economic sustainability of the country as a whole. In large energy companies, a separate service centre is responsible for payroll and payment processing, tax advice, IT and automation advice, and other services. It provides services to the corporate centre, operating companies and production enterprises within the holding. Therefore, the issue of automating payroll and social benefits is relevant for enterprises with a large number of separate divisions. In addition to the mandatory accruals and payments, energy companies may have special types of tangible and intangible remuneration, such as a grading system of remuneration, bonuses for innovation, social packages, etc., which should be reflected in the automated payroll and social benefits system. The article discusses two approaches to the automation of payroll and social benefits calculations using corporate systems SAP Payroll, SAP HCM, SAP ERP in combination with Microsoft Power BI, robotic business process automation tools and Visual Basic for Applications (VBA) macros. Automating payroll with SAP HCM and SAP ERP and using Visual Basic for Applications macros provides businesses with significant benefits, including increased efficiency and productivity; reduced risk of errors; improved data quality; and improved control and visibility. The combination of SAP ERP, robotic business process automation, and Microsoft Power BI analytics and visualisation tools allows for a visual assessment and analysis of deviations and errors in the available payroll data at energy companies. The proposed approaches were used to implement the payroll processing process, the sick leave management process, and the payroll verification process. The use of payroll and social benefits automation tools helps businesses identify any discrepancies in tax payments between different locations and cities. The visual map in Power BI gives an idea of changes in tax payments over time. Identifying inconsistencies in tax obligations helps energy companies correct errors, improve processes, and avoid financial risks.