3 facts about big data veracity you need to be aware

-

As mentioned before, the collection and analysis of big data bring five challenges to business users to deal with: Volume (which implicates different ways of storing data), Velocity (where we analyse which kind of rapidness businesses need to collect and process their data), Variety, and Veracity. The last characteristic is the one we will be discussing in this blog post, how it is important to small and medium businesses and three facts about the significance of it. 

Considered to be the most important challenge to businesses and data scientists to be worried about, data veracity means the level of trustworthy, security and consistency of the data collected and processed. (GutCheck, 2019) The data quality and applicability should be questioned and audited regularly, from the process of collection and creation to the back-end of storing and archiving. If correlated or showcased wrongly, it can cause misinterpretation and wrong actions taken. It is a characteristic that affects all the other steps of the big data analytics process, from the storage to the share stages. (AWS, no date) However, some steps do not need to be audited constantly (Archiving your data after storage, for instance) but it is important to ensure accuracy and cohesion in the analysis. 

A person checking their laptop with a pen. In the background we can see a glass, plants and the reflection of the sun.
Credit: Sigmund (Unsplash)

Thinking of that, we reunited five facts about data veracity that business owners need to be aware of to achieve desirable and coherent insights, and, therefore, consistent results.


1. Make the right questions about the data collected (AWS, no date)

Think of how the data collected should look for your company. What is useful, what is not so helpful? Understanding and knowing what kind of data the business needs to make decisions is important as it is going to keep analysis clean and effective. 

2. Low accuracy, ineffective course of actions

97% of business admitted that it was because of the quality of data read, dubious insights were generated affecting the decision making process. (Accenture, 2018) Keeping an eye closer to the process and ensuring consistency in each step is key to tackle data analytics challenges. 

3. Unchecked data is a trend vulnerability

Small and medium businesses making decisions through data analytics insights need to critically look into the kind of data collected and processed. Comprehending and assessing the data can avoid future damages to company integrity and reputation. (Accenture, 2018)


Overall, big data analytics is an extensive subject that demands attention and awareness from independent business owners. If their business requires data analytics to take actions and make decisions towards their customers, they need to be aware of the five challenges the analytics bring. Veracity is a challenge that affects all the other ones, which ensures that data has quality, consistence and be trustworthy of being collected, analysed and shared. 


Author: Sergio Augusto

#BigDataAnalytics #SmallandMediumBusiness #DataAnalyticsChallenges #DataVeracity #CompanyIntegrity #CompanyReputation 

References

'Data Analytics Fundamentals' (no date). Available at https://www.aws.training/Details/eLearning?id=35364 (Accessed: 18 February 2021)

(2018); Accenture Technology Vision 2018, Accenture [Online]. (Accessed: 9 March 2021).

'Veracity: The Most Important 'V' of Big Data' (2019). Available at https://www.gutcheckit.com/blog/veracity-big-data-v/ (Accessed: 9 March 2021).

Comments

  1. James White1 April 2021 at 07:01

    As this blog points out very well, it is crucial for a company to store its customers and operational data in a clear and consistent manner. Not only for security reason but also to ensure the data informs the companies marketing strategy correctly. Failure to have processes in place to deal with data veracity can lead to customers distrust and a loss of market share, especially for SME's. Great post Sergio! Looking forward to your next one!

    James

    ReplyDelete
  2. Natassya Coelho11 April 2021 at 04:22

    As the world moves towards automated decisions, where computers make choices instead of humans, it is imperative that organisations can rely on the quality of the data. In this context, it is essential that the data collected is real, since relying on something that does not convey confidence can lead to making bad decisions, which can not only result in financial losses but also problems with the company's reliability. Therefore, veracity is crucial for any type of business.
    Thank you so much for clarifying the importance of veracity, Sérgio!

    ReplyDelete
  3. Udit Shokeen13 April 2021 at 15:42

    This comment has been removed by the author.

    ReplyDelete
  4. Udit Shokeen15 April 2021 at 14:40

    This post actually covers everything there is to know about veracity, such a helpful post for SMEs owners. It would definitely be relatable to their business activities. The V's, in my opinion, should be considered a main dimension of success when it comes to achieving good big data results for SMEs. For SMEs, big data will open up a world of possibilities. Big data will help SMEs improve their results if they use the right techniques. In addition to social media, B2B consideration is important. The Vs are another critical consideration. Velocity and Variety are two very useful V's for SMEs, and they can have a wide range of dimensions and outcomes when applied to them.

    ReplyDelete

Post a Comment

Popular posts from this blog

The importance of Knowledge Management and how data analysis informs marketing strategies

-
Knowledge management is crucial for companies to succeed. Knowing your business and your customer’s needs, wants and behaviours help businesses to inform their marketing strategies, increase their revenue and their market share. In the digital age, the majority of this knowledge comes in the form of data. However, data gathered by businesses is unrefined and difficult to read. A large company would have thousands of rows and columns of raw data on spreadsheets which would be extremely difficult to read and impossible to draw insights from. As Steve Denning stated “Nothing can be managed unless and until it is measured.   Because knowledge per se has no value in itself, it has to be measured in relation to the strategy it is intended to accomplish. ” (Denning, 2021) . This blog will outline the knowledge management and analytics processes which transform this raw data into actionable information. The two main analytic types that companies use to analyse their data are information ...
Read more

The Importance of Data Governance and how it can help small and medium businesses succeed.

-
As we know data is a valuable asset to businesses and needs to be governed and secured in an efficient manner while complying with regulations. Firstly, we must understand and define what data governance means. “ CIO.com  put forth an excellent definition earlier this year: “Data governance defines roles, responsibilities, and processes for ensuring accountability for and ownership of data assets across the enterprise.” (Iversen, 2021) . While the primary function of data governance is to comply with regulations and address security concerns, a company can use this to improve decision making and optimise their products and services. Data governance systems can be used to organise data for specific uses and target essential KPI’s if utilised correctly. This blog will outline the benefits of an effective data governance system and how it can help businesses be successful.   A strong data governance system can benefit a business in a number of different ways. Firstly, puttin...
Read more

Two ways that data analytics can satisfy customer needs

-
Image
Even before considering using the power of data analytics for small or medium companies, the main questions should be how those analytics are going to help businesses to know their consumers, and how it can be useful and consistent to leaders and managers to make an effective application of them. This is considered one of the main challenges to independent and established owners, the value challenge. The value challenge in data analytics is relatable to the extraction of insights from the data collection and how we can interpret them. (AWS, no date)  In this case, we have two main approaches to read, comprehend and take useful outcomes from it: Prescriptive and Predictive. Both are distinct by default and serve different purposes that can enhance knowledge management within small and medium businesses. Credit: Georgia de Lotz (Unsplash) Beforehand, it is important to highlight that there are some important aspects of how giving value and generating management knowledge, as it was d...
Read more