5most commonmistakes of

DATAAcquisition

Data AcquisitionIt is the process of gathering, filtering and cleaning the data before it is put in a data warehouse or any other storage solution on which data analysis can be carried out.

Data acquisition is one of the major big data challenges

What is

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Mistake#1

It is very important to acquire data from the most relevant & credible sources, depending on your target segment

Choosing any random or all data sources available will often give you irrelevant data

In recent times, there have been drastic increase in the way data can be acquired from many new data sources.

Other types of sources can be Activity-generated data, Legacy documents,Surveys etc. All you have to do is look for the right source for your business

Internet of Things Sensor Networks

Open data onthe Web

Data from mobileapplications

social network data

Datasets insideorganizations

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Mistake#2

With new data sources,come new methods of

acquiring data

“Using the same old methods for acquiring data cannot be as effective as they used to be

It is very important to acquire data which is clean, ready to use and at the right time

Earlier, data acquisition was done manually, but now there are web scraping services available, which make your work easier & save your time

Mistake#3

Focusing on quantity will invite a lot of irrelevant data

You will waste your time & resources by acquiring data from unwanted sources

Data cleaning will become tedious & time consuming task

Data Analysis will show inaccurate results due to low quality data

It is better to have fewer data of quality than too much expandable junk

Quality

Quantity

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Improving the quality of data will result in reduced costs, improved efficiency, better insights and enables collaboration across verticals.

The right quality is the data that is complete, accurate & consistent, available, time-stamped and industry standards-based.

But obtaining high quality data is easier said than done. The best way to quickly & easily acquire data at low cost is collaborating with a good web scraping service provider.

Why

Mistake#4

Acquiring data in-house can be exhausting & will cause lot of problems if you are acquiring large amount of data

It will incur an huge additional cost to setup & configure the infrastructure needed to maintain the acquired data and upkeep & monitoring of stack

You won’t get time to focus on your core product, since you will be putting more efforts in acquiring data in-house

It will incur an additional cost of hiring experts!

• Must deliver low, predictable latency in both capturing data and in executing queries

• Should be able to handle very high transaction volumes

• Preferably in a distributed environment

• Should support flexible and dynamic data structures

Pro Tip: Let the experts acquire data for you

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Mistake#5

Data Analytics is the key, but if there is no data, there will be no analytics

There will be no increase in overall value of your product or services

You will never know what your users & others are talking about you

You will be limited in your decision making

I am goanna need you to bring more data

Without data you’re just another person with an opinion - W. Edward Deming

Data offers valuable insights for any business

Data is a crucial part of analytics which helps in decision making

Data can be used for new Customer Acquisition

You can achieve more target oriented promotions by combining diverse sources of data

Why Acquire

In short, not acquiring data will be the biggest mistake which may result in a huge business loss

Thank you