Last updated on August 28th, 2023 at 11:03 am
Data analytics is fast evolving, and with the increasing use of streaming data, machine data and big data only adds to the continuous challenges encountered during analyzing log data, enterprise application data, web information, historical data stored in documents and reports etc.
In the present day, data analyst struggle to provide a solution for business and client request. As it is, there is a substantial deficient of talent in the field of business data analysts and data scientist, with businesses continue to struggle with data reconciliation, data blending, data access, development of data analytics tools and data mining techniques.
Data analyst and data scientist are frequently unable to discover data and information required and are often unaware of the latest data analytics tools such as the self-service data prep tools assist in the improvement of productivity. Furthermore, the continuous development of advanced social technologies and with the incorporation of various social features have caused an increased expectation regarding timeliness and information availability. Similarly, users have similar enhanced expectations towards business information irrespective of where the data originates or how is it formatted. There is an increasing demand for instant access for data and the ease of sharing it with essential stakeholders.
Data socialization is the metamorphosis of data mining techniques to enhance data accessibility across companies, teams, and individuals. Data socialization is changing how business think about business data and how employees interface with business data.
Data socialization comprise of management of data platform which enables the linkage between self-service visual data preparation, automation, cataloging, data discovery and governance features with essential features common to a various social media platform. Hereby, it provides businesses with the ability to leverage social media metrics such as user ratings, discussions, recommendations, comments etc. to enable usage of data for improved decision making.
What is Data Socialisation?
It is a data analytic tool which enables business analyst, data scientist and various relevant users throughout an organization to search, reuse, and share managed data. It aids in the achievement of agility and enterprise collaboration. Data socialization allows employees to find and utilize data which is accessible to them within a specified data ecosystem and assist in the creation of a social network of raw data sets which are curated and certified. These data ecosystems have various levels of controls, restrictions, and limitations which can be well defined for each individual person in an organization. These data mining techniques aid the strengthening an environment of data access, wherein analyst and users are allowed to learn from one another, enhance productivity and be well-connected as its sources, cleans and prepares of data analytics.
Some Characteristics of Data Socialisation
Some of the critical characteristics of data socialization include:
- The ability of understanding data with regards to its relevance about how a particular data is deemed to be used by various users within an enterprise.
- Involvement of collaboration of essential users with the data set to harness knowledge which often remains unshared.
- It enables enterprise users to search for data which has been cataloged, prepare data models, and index metadata by users, type, application, and various unique parameters.
- Data Socialisation enables to perform a data quality score, suggest for relevant data sources, automatically recommend actions for preparing actions designed according to user persona.
With various business applications incorporating features of social media functions towards improvement in business collaboration, at this moment making individuals and companies well informed, productive and agile.
Data socialization aids in delivering various benefits to various data analytics tools and removal of obstacles towards accessing and sharing data, at this moment allowing data scientist, business users and business information analyst in improving their productivity and decision-making. It further empowers analyst, data scientist and other business users across various departments to collaborate using the available data. By providing the right person with the correct data required to make informed, educated and timely decisions, the implementation of Data socialization is deemed to be the next big thing in data analytics.
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