Research in information science and scholarly communication strongly relies on the availability of openly accessible datasets of metadata and, where possible, their relative payloads. To this end, CrossRef plays a pivotal role by providing free access to its entire metadata collection, and allowing other initiatives to link and enrich its information. Therefore, a number of key pieces of information result scattered across diverse datasets and resources freely available online. As a result of this fragmentation, researchers in this domain end up struggling with daily integration problems producing a plethora of ad-hoc datasets, therefore incurring in a waste of time, resources, and infringing open science best practices.

The latest DOIBoost release is a metadata collection that enriches CrossRef (October 2019 release: 108,048,986 publication records) with inputs from Microsoft Academic Graph (October 2019 release: 76,171,072 publication records), ORCID (October 2019 release: 12,642,131 publication records), and Unpaywall (August 2019 release: 26,589,869 publication records) for the purpose of supporting high-quality and robust research experiments. As a result of DOIBoost, CrossRef records have been "boosted" as follows:

• 47,254,618 CrossRef records have been enriched with an abstract from MAG;
• 33,279,428 CrossRef records have been enriched with an affiliation from MAG and/or ORCID;
• 509,588 CrossRef records have been enriched with an ORCID identifier from ORCID.

This entry consists of two files: doiboost_dump-2019-11-27.tar (contains a set of partXYZ.gz files, each one containing the JSON files relative to the enriched CrossRef records), a schemaAndSample.zip, and termsOfUse.doc (contains details on the terms of use of DOIBoost).

Note that this records comes with two relationships to other results of this experiment:

1. link to the data paper: for more information on how the dataset is (and can be) generated;
2. link to the software: to repeat the experiment

Analyzing sales data is essential for any business looking to make informed decisions and optimize its operations. In this project, we will utilize Microsoft Excel and Power Query to conduct a comprehensive analysis of Superstore sales data. Our primary objectives will be to establish meaningful connections between various data sheets, ensure data quality, and calculate critical metrics such as the Cost of Goods Sold (COGS) and discount values. Below are the key steps and elements of this analysis:

1- Data Import and Transformation:

• Gather and import relevant sales data from various sources into Excel.
• Utilize Power Query to clean, transform, and structure the data for analysis.
• Merge and link different data sheets to create a cohesive dataset, ensuring that all data fields are connected logically.

2- Data Quality Assessment:

• Perform data quality checks to identify and address issues like missing values, duplicates, outliers, and data inconsistencies.
• Standardize data formats and ensure that all data is in a consistent, usable state.

3- Calculating COGS:

• Determine the Cost of Goods Sold (COGS) for each product sold by considering factors like purchase price, shipping costs, and any additional expenses.
• Apply appropriate formulas and calculations to determine COGS accurately.

4- Discount Analysis:

• Analyze the discount values offered on products to understand their impact on sales and profitability.
• Calculate the average discount percentage, identify trends, and visualize the data using charts or graphs.

5- Sales Metrics:

• Calculate and analyze various sales metrics, such as total revenue, profit margins, and sales growth.
• Utilize Excel functions to compute these metrics and create visuals for better insights.

6- Visualization:

• Create visualizations, such as charts, graphs, and pivot tables, to present the data in an understandable and actionable format.
• Visual representations can help identify trends, outliers, and patterns in the data.

7- Report Generation:

• Compile the findings and insights into a well-structured report or dashboard, making it easy for stakeholders to understand and make informed decisions.

Throughout this analysis, the goal is to provide a clear and comprehensive understanding of the Superstore's sales performance. By using Excel and Power Query, we can efficiently manage and analyze the data, ensuring that the insights gained contribute to the store's growth and success.

Other-Operating-Expenses Time Series for TATA TELESERVICES (MAHARASHTRA) LTD.. Tata Teleservices (Maharashtra) Limited provides wire line voice, data, and managed telecom services to enterprise customers in Maharashtra and Goa. The company offers its information and communication solutions under the Tata Tele Business Services brand name. Its portfolio includes smart digital solutions, including collaborative and productivity services, such as Microsoft 365, Microsoft Copilot for Microsoft 365, google workspace, Zoom, and international bridging service; cloud infrastructure solutions, comprising Microsoft Azure and managed cloud services; cybersecurity solutions, including email security, endpoint security, and data loss prevention; and managed internet services. In addition, the company offers business communication solutions, such as integrated solutions, which includes Smartflo CCaaS and UCaaS; inbound communications, such as smart single number solution, SIP Trunk, toll free services, call register services, and PRI; and outbound and marketing communications, including WhatsApp business platform, SMS solutions, Smartflo OBD, and truecaller verified business caller ID. Further, it provides network and connectivity solutions, comprising internet leased line, consisting of smart internet leased line and ILL burstable bandwidth; smart WAN, such as SD-WAN iFLX and EZ cloud connect; SmartOffice and broadband; and P2P leased line, ultra-LOLA, and business Wi-Fi. The company serves BFSI, IT/ITES, manufacturing, services, education, healthcare, telecom, media, entertainment, retail, and other industries. Tata Teleservices (Maharashtra) Limited was incorporated in 1995 and is based in Navi Mumbai, India.