In fact, big data is diverse and unstructured, therefore it requires special tools and techniques that go beyond traditional information system and relational databases solutions.
Indeed, big data comes from various sources [ 23, 36].
Emerging data collection technologies provide a multitude of rich data from diverse data sources.
Further progress depends on expanding informatics capacity and standardizing data formats to integrate massive volumes of clinical, genomic, proteomic, and immunomic data from diverse institutions.
The initiative collects data from diverse sources including education data, health data, regional surveys and population surveys.
The HSTSM modelling approach incorporates a number of soft computing techniques such as: deep belief networks, auto-encoders, agglomerative hierarchical clustering and temporal sequence processing, in order to address the computational challenges arising from analysing and processing large volumes of diverse data to provide an effective big data analytics tool for diverse application areas.
'Big data' refers to large, diverse, complex, longitudinal, and distributed data sets generated from instruments, sensors, internet transactions, email, video, click streams, and other digital sources available today and in the future.
Big data refers to large, diverse, complex, longitudinal, and distributed data sets.
Security analytics is more than just big data – it's also diverse data.
With the transformative role, big data has played in diverse settings, there is a lot of interest in harnessing the power of big data for development and social good.
