Question: What type of music does Big Data and Underworld have in common?
Context: Underworld are a British electronic group formed in 1980 in Cardiff and the principal name under which musicians Karl Hyde and Rick Smith have recorded together.  Darren Price has toured with the band since 2005, after the departure of Darren Emerson in 2000.  Known for visual style and dynamic live performances, Underworld have influenced a wide range of artists and been featured in soundtracks and scores for films, television and the 2012 Summer Olympics in London. Big Data is an American electronic music project created by producer, Alan Wilkis.  Big Data is best known for its single "Dangerous", featuring Joywave, which reached number one on the "Billboard" Alternative Songs chart in August 2014, and was certified gold by the RIAA in May 2015. Industrial big data refers to a large amount of diversified time series generated at a high speed by industrial equipment, known as the Internet of thingsThe term emerged in 2012 along with the concept of "Industry 4.0”, and refers to big data”, popular in information technology marketing, in that data created by industrial equipment might hold more potential business values.  Industrial big data takes advantage of industrial Internet technology.  It uses raw data to support management decision making, so to reduce costs in maintenance and improve customer service. Yasaman (Yassi) Hadjibashi is a business, data and technology executive.  She currently leads, defines and executes the innvoation agenda for Barclays Africa Group including the RISE Innovation Hub in Cape Town as their Group Chief Creation Officer.  Formerly the group's first ever Chief Data Officer, she led their big data transformation across the African continent, launching an award-winning portfolio of data products.  She joined Barclays in 2010 and has worked in senior management positions in product innovation and execution across digital and mobile, as well as client/customer experience and design.  She has been fundamental in establishing big data capabilities as a group-wide function across Barclays, whilst defining the bank’s next generation Data strategy and driving the execution of a number of key big data initiatives. A data set (or dataset, although this spelling is not present in many contemporary dictionaries like Merriam-Webster) is a collection of data.  Most commonly a data set corresponds to the contents of a single database table, or a single statistical data matrix, where every column of the table represents a particular variable, and each row corresponds to a given member of the data set in question.  The data set lists values for each of the variables, such as height and weight of an object, for each member of the data set.  Each value is known as a datum.  The data set may comprise data for one or more members, corresponding to the number of rows.  The term data set may also be used more loosely, to refer to the data in a collection of closely related tables, corresponding to a particular experiment or event.  An example of this type is the data sets collected by space agencies performing experiments with instruments aboard space probes. Data sets that are so large that traditional data processing applications are inadequate to deal with them are known as big data. Critical data studies is the systematic study of data and its criticisms.  The field was named by scholars Craig Dalton and Jim Thatcher in their 2015 article titled "What does a critical data studies look like, and why do we care?"  Interest has developed in this domain as a response to the emergence and reliance on 'big data' in contemporary society.  Some of the other key scholars in this discipline include Rob Kitchin and Tracey P. Lauriault.  Scholars have attempted to make sense of data through different theoretical frameworks, some of which include analyzing data technically, ethically, politically/economically, temporally/spatially, and philosophically.  Some of the key academic journals related to critical data studies include the "Journal of Big Data" and "Big Data and Society". Security Visualisation is a subject that broadly covers the aspect of Big Data, Visualisation, human perception and Security.  Each day, we are collecting more and more data in the form log files and it is often meaningless if the data is not analyzed thoroughly.  Big Data mining techniques like Map Reduce help narrow down the search for meaning in vast data.  Data visualisation is a data analytics technique, which is used to engage the human brain into finding patterns in data. Randy Bean (born 1956) is a business executive, author, speaker, thought-leader, and chief executive officer of NewVantage Partners LLC, a strategic advisory and management consulting firm which he co-founded in 2001, with offices in Boston, New York, San Francisco, Austin, and Charlotte.  Bean maintains an active involvement in philanthropic and civic affairs, and is a patron and board member of national and community organizations in Boston (MA), Stonington (CT), and St. Louis (MO).  Bean is also the founder and executive director of the Big Data for Social Justice Foundation, a non-profit foundation established in 2016 with the goal of raising awareness of data-driven social justice initiatives and the application of Big Data to global and community issues in the areas of disease, famine, social inequality, and criminal justice disparities.  As a writer and commentator, Bean is known for his observations on the impact of data and analytics on business culture and innovation, and on the emergence of Big Data as a force for business transformation and disruption.  He has also written on the social impact of Big Data. Big Data Maturity Models (BDMM) are the artefacts used to measure Big Data maturity.  These models help organizations to create structure around their Big Data capabilities and to identify where to start.  They provide tools that assist organizations to define goals around their big data program and to communicate their big data vision to the entire organization.  BDMMs also provide a methodology to measure and monitor the state of a company’s big data capability, the effort required to complete their current stage or phase of maturity and to progress to the next stage.  Additionally, BDMMs measure and manage the speed of both the progress and adoption of big data programs in the organization. Reynold Xin is a computer scientist and engineer specializing in big data, distributed systems, and cloud computing.  He is a co-founder and Chief Architect of Databricks.  He is a frequent speaker on the topic of Big Data and open source software at conferences.  He is best known for his work on Apache Spark, which as of 2016 is the top open-source Big Data project.  He designed and lead development of the GraphX, Project Tungsten, and Structured Streaming components and he co-designed DataFrames—all of which are part of the core Apache Spark distribution—plus served as the release manager for Spark's 2.0 release.  s of 2016 he is also the most active contributor to Spark with over 1000 commits.
Answer: electronic