Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Trends of digitalization and adoption of big data & analytics among UK
  SMEs: Analysis and lessons drawn from a case study of 53 SMEs   Small and Medium Enterprises (SMEs) now generate digital data at an
unprecedented rate from online transactions, social media marketing and
associated customer interactions, online product or service reviews and
feedback, clinical diagnosis, Internet of Things (IoT) sensors, and production
processes. All these forms of data can be transformed into monetary value if
put into a proper data value chain. This requires both skills and IT
investments for the long-term benefit of businesses. However, such spending is
beyond the capacity of most SMEs due to their limited resources and restricted
access to finances. This paper presents lessons learned from a case study of 53
UK SMEs, mostly from the West Midlands region of England, supported as part of
a 3-year ERDF project, Big Data Corridor, in the areas of big data management,
analytics and related IT issues. Based on our study's sample companies, several
perspectives including the digital technology trends, challenges facing the UK
SMEs, and the state of their adoption in data analytics and big data, are
presented in the paper.

2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas