CollaboratIve approaches needed to close the big data skIlls gap

Question 1

Define Information Strategy

Answer 1

Information strategy is an emerging discipline that concerns itself with all aspects of data as a business asset

Question 2

What do businesses look for in data professionals?

Answer 2

Businesses, need data professionals with broader and deeper analytics skills that enable them to tackle the full breadth of today’s data management technologies and challenges, including security, privacy, master data, hadoop, real-time streaming data, real- time predictive analytics, cloud, and mobile.

Question 3

What does a data engineer do?

Answer 3

the data engineer has deep knowledge of relational databases and NosQl databases such as hadoop, can integrate data from diverse data sources, and can design data-driven services.

Question 4

What technique is often used to protect the privacy of individuals?

Answer 4

De-identification by deleting or obscuring actual names, addresses, social security numbers, and other data elements which uniquely identify individuals.

However, simple de-identification techniques are often insufficient to protect privacy in the age of big data since it is often possible to re-identify individuals by combining data from multiple public sources with your de-identified data

Question 5

What is the best talent development approach for business and academia?

Answer 5

Business and academia must collaborate to clearly define the big data knowledge and skill sets required across the organization. every profession, whether business or technical, will be impacted by big data and analytics

Question 6

academia, industry, and government should join together to create a national consortium to address the big data and analytics skills challenge. that consortium would:

(answer with 5+ tasks)

Answer 6

• Create formal definitions of prioritized jobs such as data scientist, information
• establish curriculum requirements and accreditation standards for programs designed to produce the required knowledge and skills for specialty jobs. Use workforce analytics (ringo, 2012) to provide actionable feedback to ensure that curricula rapidly
evolve to meet the evolving needs of industry.
• set minimum standards for data and analytics literacy required by all students in the
age of big data. Create and deliver literacy training via massive online open courses
(MOOCs).
• Create open online communities around shared interests to engage industry,
government, and academia.
• partner with industry organizations such as It-ology and the National Consortium
for Data science (National Consortium for Data science, 2014) to establish strong
internship programs and increase collaboration between business and academia.
• Foster the creation of textbooks and courseware to address both literacy and
specialized skills at all levels from undergraduate to executive education.
• establish working groups to address key data policy issues such as information
security, individual privacy, and the ethical use of big data.