Big Data Basic Terms You Should Know in the Era of Big Data Analytics

This post is for those people who wants to speak fluent ‘data-ese’. You will agree with me that knowing the basic terms in big data is something you cannot do without. Therefore, here are a few words (4 precisely) to add to your vocabulary this week. These are the 4 Basic Terms You Need to Know in the Era of Big Data.

Big Data Basic Terms

1. Data-as-a-Service (DaaS):

DaaS is a highly customised marketing asset that is made up of Hard-to-Find-Data (HTFD). These are unique data that provide an unbroken stream of qualified leads. it is known that these leads are picked up by their digital footprints and in real-time. As a matter of fact, you can offer them your products depending on their online behaviour. You can do this even if they are not particularly looking to buy something online.

2. Siloed Data:

We can say that a data silo is a dump-yard for data. Even though this statement may sound harsh, a lot of companies have separate data silos for different departments. the data silos are not integrated which each other, which renders the data completely dead. Take a good example; one department team of staff may use the contact details to target a client, while not knowing their buying power or purchase history. Conversely, this may lead to the client feeling unappreciated, and eventually the loss of a business lead. Therefore, integrated silos make the data come alive in a firm, and reduce the chances of disconnected behaviour that may impact the organisation in the long run.

3. Fast Data:

Explanation for fast data goes thus; When Big Data is continually processed to reveal insights in real time, you get fast data to act speedily. Please bear in mind that it is different from DaaS (Data-as-a-Service). This is different in the sense that as the latter gives you leads in real time, the former gives you the opinions, events, and choices that are popular in the present moment. However, as customers look up for your products or your competitors’, make transactions/purchases, post statuses, book flights, or tweet hashtags, you know where the action is required. You will agree that this gives you an incredible competitive edge. It is important for targeting in-market users and businesses to up your return of investment (ROI).

4. Dirty Data:

In the year 2014, Ascend2 did a survey which revealed that almost 36 percent marketers believed dirty data. Or data which is inaccurate or outdated – is the major cause of failed marketing automation. Data decays at the rate of two percent, which might not seem much to you unless you translate it numerically: in every 30 minutes, 7about seventy five phone numbers and one hundred and twenty business addresses change. Also, about thirty CEOs change jobs; and thirty new businesses crop up. Little wonder then that dirty data is the major reason for Customer Relationship Management (CRM) failure. Wrong data means losing out on customers: either by not being able to contact them due to wrong communication information or by losing their trust by presenting them incorrect data.

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