Big Data is a great companion for every business when it comes to analytics. However, coping with the two can be pretty confusing if you are not careful. Big Data and analytics go hand in hand, and if you are smart enough to avoid some common mistakes when it comes to working with both, you are bound to gain a strategic edge in the market with success. So it is important that you have clarity about this.

What are Big Data mistakes that you should look out for?

Expert DBA specialists emphasize that Big Data is an invaluable resource for modern businesses today. Irrespective of how big or small the company is, this data helps you gain insights that can transform your business’s fate. Specialists in data administration and management add that if a company does not have a good strategy for data management, it will lose out on salient business opportunities in the market. Moreover, the value of the business drops, which is detrimental to the company’s progress and development.

Big Data with analytics is a promising investment for any business as it allows it to process large sets of data to get invaluable insights. However, when a business leverages this data, it brings with it confusion that deters the business from achieving its optimal potential. So, before commencing any data project, businesses should consider the following top mistakes when it comes to Big Data and avoid them at all costs-

  1. Depending on the same key performance indicators or KPIs – The business environment is a dynamic one and businesses should adapt to the change as and when the time arises. They should introduce new solutions and strategies that help them cope with the demands in the market. However, most businesses continue with the traditional key performance indicators that keep them away from progress and exploring new technologies and tools. To progress and progress in the dynamic digital eco-system, companies need to deploy novel and extra tools suitable for data analytics for reflecting the business’s present performance so that they can correctly identify what will drive the business forward successfully.
  2. Lack of concern for data security – Governance and security are key concerns for any business. While companies are now embracing projects that focus on Big Data and analytics, they progress towards it with a lack of governance and security. In this respect, they need to be aware and consider embracing a multi-faceted approach to help them secure Big Data. The business should understand the nature of the processed data, audit the manipulations of this data, and maintain control over-privileged users. Besides the above, the business should hold conversations that revolve around security, governance, and compliance at the Big Data project’s outset.
  3. Paying attention to the technical costs only – Specialists from renowned company in database management, consulting, and administration remotedba says that to get any data project off the ground, the business should accept change. Still, unfortunately, this approach is underestimated to a large extent. It is so grave that it does the business more harm than good. The business should plan the technical costs before deploying a data strategy; however, it generally overlooks the need to budget those items beyond the technical costs. This is a major mistake that most companies make. It is prudent for the business to plan the budget to develop skills, training, and change management in the company that results in a cultural change to ensure the effective optimization of Big Data with analytics.
  4. Overlook the external data – Today, you will see that data comes from multiple sources and in several forms than just spreadsheets and database systems. Most of the data that the business collects is not structured, and this raw data is often in the form of audio recordings, photographs, text files, and more. It is the need of the company to have a strategy for maintaining robust data in place. This applies to both structured and unstructured data that give the business meaningful insights. However, when this external data is overlooked, data projects come to a sudden halt. This raw data sources can also be obtained from data brokers, data repositories, and governments. They should deliberate every data source for delivering value for the company.
  5. Not resolving genuine data science problems – There is a major misconception among business leaders that they are well acquainted with data science and other associated things like algorithms’ development just because they have recruited data scientists. However, data scientists generally spend a lot of their time assessing and later cleaning the data before integrating it with other data sources. It is the need of the hour for the business to understand how data scientists are spending their time completely. It is prudent for them to have a defined and clear strategy for maintaining data cleaning and integration. This is where they should have a data officer on their pay-roll to address the company’s data science problems.
  6. Not planning for artificial intelligence and machine intelligence to be disruptive – Both AI and ML have a significant impact on the business world today in all industries. Both of these technologies will disrupt all the aspects of conventional businesses to boost employee productivity and operations. However, several businesses still fail to understand the potent impact of AI and ML technologies. This means that those companies that want to be at the disruptive end of artificial intelligence should be willing to pay for talent. This implies they must pay human resources dealing with AI and MI technology experience and expertise higher so that they can become disruptors of conventional business practices and not be disrupted by the progress of these technologies.

Therefore, companies should be careful about the common ones listed above when it comes to Big Data mistakes. They should resort to professional remote DBA consulting services to get an accurate understanding of how to mitigate these errors to combine Big Data and analytics successfully together for their companies’ progress.

Walter Moore is a blogger and digital marketing expert. He is quite experienced in the field of web marketing as well as website designing. He has been working as a database administrator in the IT industry RemoteDBA. His research has helped thousands of users and brands with marketing campaigns too.

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