Free cookie consent management tool by TermsFeed Blog - Why data matters | Redline Group Recruitment News and Blogs | Redline Group Ltd

Why data matters

 The data on data

  • The big data analytics market is expected to be worth £73 billion by 2023.
  • The average person generates 1.7 megabytes of data a second.
  • Internet users generate around 2.5 quintillion bytes of data a day.
  • 97.2% of organisations are now investing in big data.
  • 95% say managing unstructured data is a problem for them.
  • 80-90% of the data we generate is unstructured.

Why is data valuable?

Put simply, knowledge is power. Data can be exchanged for money. Giants like Amazon and Google have learned to view data as a valuable asset: data capital.

The ubiquity of social media and rapid digital data transfer makes obtaining data both quick and easy. The company that controls the data will control the market. This creates fierce competition and what’s known as the data imperative: the more rapidly data is produced, the more companies clamour for it.

However, obtaining data is only half the picture; the other half is what companies do with it. Unstructured data has little value; it needs to be boiled down into a form that can be used to profile users for targeted advertising etc. This means getting down to the finer details of individuals’ likes, political leanings, marital status, social status, earnings, etc.

The benefits of good quality data include:

  • Improve customer experience.
  • Better decision making
  • Organisations can be more proactive rather than reactive.
  • Find solutions to problems.
  • The ability to measure the effectiveness of a strategy.
  • Help manufacturing industry achieve net zero

When is the data a problem?

Data extraction methods can be ruthless, and personal data can be used to attack individuals through blackmail or by damaging their reputations. Terrorists can use data to find potential recruits, and political parties can use data to sway elections and undermine democracy.

In 2017, news broke that up to 87 million Facebook users’ personal data had been harvested without their consent by British firm Cambridge Analytica. The company had already had the data for three years. In that time, it had been used to create personally targeted ads to influence those users to vote for Donald Trump, Ted Cruz, and allegedly, Brexit.

How do you decide which data is worth collecting?

First, define the whole scope of possible master data you need to choose from – your Master Data Management. This could be thousands of data objects.

From those, look at which ones are consistent. For example, if you’re developing a new product, the important figures are the ones that stay stable through the whole cycle of product development, that describe the core entities of your organisation as they are used in different business processes. Traditionally, you also need to look for data that is not transactional but stable along the value chain.

What can data integration do for a company?

Primarily, data integration gets rid of data silos. Instead of each department having its separate data with little communication between departments, everyone can have an overview of the whole picture. However, there is another advantage to data integration: it also overcomes functional silos, where each department has its separate people and processes for doing the same things, often reinventing the wheel rather than learning from each other.

Data creates a common understanding of the data objects and the relationships between them and makes it possible to create an overarching data model for a product, brand, or organisation. Data-driven insights allow businesses to make more strategic decisions and to add more value.

With the growth in Big Data, plus the rapidly evolving methods for analysing data, the importance of data across every aspect of business will only increase. Those companies that view data as a strategic asset and develop robust data and analytics strategies are the ones that are likely to succeed in this new data-driven world.

The sorts of careers and software jobs in Big Data include Data Scientist, Data Engineer, Data Analyst, and Security Engineer.


Fill out the form below to let us know about a vacancy you would like us to advertise for you.

Click here


Register your details to access the latest vacancies, create job alerts and much more.