Major Big Data Issues in Australia: Focus Shifts to AI Engineers and Data Scientists

Big Data and AI have permeated all the realms of business in Australia. Thinking of starting and sustaining a business today without AI and Big Data is simply impossible. However complex, it may sound, learning and working with Big Data is really productive. In its current evolving state, Big Data faces some major challenges.

Here are 3 major challenges that are hurting Big Data adoption and its future prospects in Australia.

Big Data and the Rate of Decay

It is said that business data such as Contacts, Email IDs and Company names decay at the rate of 30% per year. With the kind of Big Data volume we see and work with, this rate of decay could be 50% or even higher.

Data Decay refers to the rampaging rate of degradation of data due to obsolete updates, non-validation and inaccurate information. Data collected from mobile and telecom companies, email servers, landing pages and other Customer Relationship Management platforms face upgrade issues due to Data Decay.

With Big Data Training, you will be able to work with various databases that suffer from the perennial problems of decay. This provides AI Engineers and Big Data Architects in Australia to implement data quality standards using analytics, BI and Data Compliance benchmarks.

Third Party versus First Party Data

No matter which business you run in Australia, Big Data would be central to your Operations. In a simple data management system, you will be working with three types of data, classified in terms of ownership.

These are:

  • First Party Data
  • Second Party Data
  • Third Party Data

First Party Data is the safest way to gain traction in the Big Data and AI industry of Australia—as you have full ownership and discipline in how you plan to leverage this information in your various systems.

However, some Big Data analysts disagree and argue that it’s best to work with Third Party and First Party Data. Reason: With these mix of data types, you can build 360-degree customer relationships and generate high-quality data sources in the future from new contacts. That’s just one example.

Lotame says that it’s very important to enhance your first party data; combine with your third-party data.

Imagine the control you have on the market dynamics, when you have understood the concept of Data Decay and apply it to the various data types. AI engineers can help data management companies in Sydney, Melbourne and other parts of Australia to build and activate Big Data filters.

Cost and Management of Big Data Storage

Storage and maintenance of Big Data hygiene remain the biggest Big Data challenge. Most often, you will be working on a hyperscale data storage and computing environment.

With new Big Data sources comes a cost of opportunity and threats; and these costs are mostly hidden in the way human managers treat them! That’s where the role of AI and Big Data engineers are yet to be fully appreciated.

Sadly, these skills remain underpaid and under-valued in Australia.

Conclusion

Within a decade of its adoption, Big Data architecture has moved away from primarily an Enterprise scale resource to becoming the central driving force across a diverse range of sectors, industries and markets. In the digitized grid of Big Data, Big Data training in Australia can compound advantages and help to blow these challenges effectively.

 

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