Aruna Balakrishnan

Bio: Aruna Balakrishnan is an academic researcher from Google. The author has contributed to research in topics: Enterprise data management & Enterprise software. The author has an hindex of 2, co-authored 4 publications receiving 46 citations.

From Data to Insight Work Practices of Analysts in the Enterprise

Abstract: With greater availability of data, businesses are increasingly becoming data-driven enterprises, establishing standards for data acquisition, processing, infrastructure, and decision making. Enterprises now have people dedicated to performing analytic work to support decision makers. To better understand analytic work, particularly the role of enterprise business analysts, researchers interviewed 34 analysts at a large corporation. Analytical work occurred in an ecosystem of data, tools, and people; the ecosystem's overall quality and efficiency depended on the amount of coordination and collaboration. Analysts were the bridge between business and IT, closing the semantic gap between datasets, tools, and people. This article provides an overview of the analytic work in the enterprise, describing challenges in data, tools, and practices and identifying opportunities for new tools for collaborative analytics.

Methods for generating notifications in a shared workspace

Abstract: A method includes providing, by a server computer, a shared workspace for facilitating collaborative work by a plurality of users. The method also includes monitoring information associated with the shared workspace, the information relating to each user from the plurality of users. The method also includes determining whether a notification definition is satisfied, the notification definition based at least in part on the information associated with the shared workspace, and outputting, for display to at least one user from the plurality of users, a notification, in response to determining that the notification definition is satisfied.

From Dorms to Cubicles: How Recent Graduates Communicate

Abstract: In a two-part field study, we studied the communication tool use of 29 college students and 20 recent college graduates. In comparing the two groups' communication choices, we explored how transitioning from attending college to working full time impacts communication. We discuss how communication changes for recent college graduates in terms of both the content of their conversations, as well as the communication methods they use. We found that convenience plays a major role in the adoption and usage of communication tools, with participants preferring methods that were easily accessible at work, at home and in transit. We identify life changes recent graduates experience as they transition into emerging adulthood: the effect of being on a computer at work all day, changing social circles and scenes, being geographically distant from friends and family, and the desire for a professional persona. We discuss the impact of these changes on communication.

Networked desktop environment

Abstract: A method and apparatus for a networked desktop environment is provided. Executing a networked desktop environment may include identifying a networked desktop state of the networked desktop environment, which may include a networked desktop workspace and an information element. The networked desktop state may include information indicating a multi-dimensional position of a representation of the information element in the networked desktop workspace. Executing the networked desktop environment may include generating instructions for use in rendering the networked desktop workspace, which may include information indicative of the networked desktop state, and transmitting the instructions to an interface device. Information indicating an interaction with the networked desktop environment may be received and the networked desktop state may be updated based on the interaction information.

Futzing and Moseying: Interviews with Professional Data Analysts on Exploration Practices

Abstract: We report the results of interviewing thirty professional data analysts working in a range of industrial, academic, and regulatory environments. This study focuses on participants' descriptions of exploratory activities and tool usage in these activities. Highlights of the findings include: distinctions between exploration as a precursor to more directed analysis versus truly open-ended exploration; confirmation that some analysts see “finding something interesting” as a valid goal of data exploration while others explicitly disavow this goal; conflicting views about the role of intelligent tools in data exploration; and pervasive use of visualization for exploration, but with only a subset using direct manipulation interfaces. These findings provide guidelines for future tool development, as well as a better understanding of the meaning of the term “data exploration” based on the words of practitioners “in the wild.”

An ROI-based review of HR analytics: practical implementation tools

Abstract: The purpose of this paper is to provide a return on investment (ROI) based review of human resources (HR) analytics. The objectives of this paper are twofold: first, to offer an integrative analysis of the literature on the topic of HR analytics in order to provide scholars and practitioners a comprehensive yet practical ROI-based view on the topic; second, to provide practical implementation tools in order to assist decision makers concerning questions of whether and in which format to implement HR analytics by highlighting specific directions as to where the expected ROI may be found.,This paper is a review paper in which a four-step review and analysis methodology is implemented.,Study results indicate that empirical and conceptual studies in HR analytics generate higher ROI compared to technical- and case-based studies. Additionally, study results indicate that workforce planning and recruitment and selection are two HR tasks, which yield the highest ROI.,The results of this study provide practical information for HR professionals aiming to adopt HR analytics. The ROI-based approach to HR analytics presented in this study provides a robust tool to compare and contrast different dilemma and associated value that can be derived from conducting the various types of HR analytics projects.,A framework is presented that aggregates the findings and clarifies how various HR analytics tools influence ROI and how these relationships can be explained.

LabBook: Metadata-driven social collaborative data analysis

Abstract: Open data analysis platforms are being adopted to support collaboration in science and business. Studies suggest that analytic work in an enterprise occurs in a complex ecosystem of people, data, and software working in a coordinated manner. These studies also point to friction between the elements of this ecosystem that reduces user productivity and quality of work. LabBook is an open, social, and collaborative data analysis platform designed explicitly to reduce this friction and accelerate discovery. Its goal is to help users leverage each other's knowledge and experience to find the data, tools and collaborators they need to integrate, visualize, and analyze data. The key insight is to collect and use more metadata about all elements of the analytic ecosystem by means of an architecture and user experience that reduce the cost of contributing such metadata. We demonstrate how metadata can be exploited to improve the collaborative user experience and facilitate collaborative data integration and recommendations. We describe a specific use case and discuss several design issues concerning the capture, representation, querying and use of metadata.

Commercial Visual Analytics Systems–Advances in the Big Data Analytics Field

Abstract: Five years after the first state-of-the-art report on Commercial Visual Analytics Systems we present a reevaluation of the Big Data Analytics field. We build on the success of the 2012 survey, which was influential even beyond the boundaries of the InfoVis and Visual Analytics (VA) community. While the field has matured significantly since the original survey, we find that innovation and research-driven development are increasingly sacrificed to satisfy a wide range of user groups. We evaluate new product versions on established evaluation criteria, such as available features, performance, and usability, to extend on and assure comparability with the previous survey. We also investigate previously unavailable products to paint a more complete picture of the commercial VA landscape. Furthermore, we introduce novel measures, like suitability for specific user groups and the ability to handle complex data types, and undertake a new case study to highlight innovative features. We explore the achievements in the commercial sector in addressing VA challenges and propose novel developments that should be on systems’ roadmaps in the coming years.

Business-driven data analytics: A conceptual modeling framework

Abstract: The effective development of advanced data analytics solutions requires tackling challenges such as eliciting analytical requirements, designing the machine learning solution, and ensuring the alignment between analytics initiatives and business strategies, among others. The use of conceptual modeling methods and techniques is seen to be of considerable value in overcoming such challenges. This paper proposes a modeling framework (including a set of metamodels and a set of design catalogues) for requirements analysis and design of data analytics systems. It consists of three complementary modeling views: business view, analytics design view, and data preparation view. These views are linked together to connect enterprise strategies to analytics algorithms and to data preparation activities. The framework includes a set of design catalogues that codify and represent an organized body of business analytics design knowledge. As the first attempt to validate the framework, three real-world data analytics case studies are used to illustrate the expressiveness and usability of the framework. Findings suggest that the framework provides an adequate set of concepts to support the design and implementation of analytics solutions.