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With the massive digitization that we are witnessing around the planet, businesses now have a lot more to account for when it comes to formulating strategies. Newer technologies and techniques are enabling enterprises to grow by leaps and bounds.

Big Data is one of the biggest technological advances in this decade, leading industries to uncharted territories and futuristic trends.

7 Best Practices for Big Data

With the wide field and scope of big data, it is paramount to have a strong foothold in foundational approaches, skills and processes. It is equally important to acknowledge that it is a rapidly evolving technology, hence it is necessary to experiment and then determine which is the best fit technique suited exclusively for your enterprise. This can be a great way to ensure that your Big Data management efforts bear fruit and you are able to leverage it to its full potential.

Big Data Management Basics

Businesses are waking up to the fact that the world is leaving an influential digital footprint. With the advent of mobile devices, cloud technology and social platforms, a humongous amount of data is generated every day, adding to the Big Data pool. To make sense of this large mass of data, companies need to have a data management strategy in place. 

With various data extraction technologies available at hand, extracting the right data is no longer a challenge. The unstructured and structured data must then be correctly sorted and stored at the right place, in the right order for it to make sense later. Big Data management, when carried out effectively, can generate insights that can be instrumental to the business’ success. Tailoring the tool and technique specifically for your company allows you to have a clearly defined path

7 Best Practices

Thinkers, innovators and industry leaders have all formulated clear Big Data management practices for their businesses. Taking a cue from the best practices, we have put together these seven important points:

1. Having a clearly defined business problem you want to solve with Big Data

It is the first and foremost requirement for effective Big Data management. Many businesses believe that Big Data is crucial for their success and spend time and resources trying to harness it without clear visibility of outcomes expected.

Start by identifying a business problem or requirement that you are trying to solve for via Big Data. Whether it is market research, market trends, data analytics marketing or else, clearly defining your scope prior delving into Big Data management is an essential step for your efforts to succeed.

2. Determining your business value and mission and connecting your Big Data Management efforts to actionable insights

This is another valuable step that you can take to ensure that your Big Data project bears fruit and helps you achieve success. After defining your business problem, it is time to also quantify and better understand the solution that Big Data can provide. Establishing a clear ROI expectation is tantamount to finding the correct justification for your Big Data project. It is extremely important to link the justification and ROI of Big Data management projects into core business objectives from the very outset.

3. Understanding how efficient Big Data Management helps your business use Big Data more effectively

Data extraction technologies, the processing of structured data sets and Big Data management are all mutually symbiotic parts of the same process. When it comes to an organization, the most important content that you can ever have access to is master data that is well structured.

Managing this foundational data effectively lays the foundation stone for effective data management, and will equip your business to scale its data processing and management capabilities up or down, depending on the amount of data flowing in from the world of Big Data. Big Data management should always keep in mind the broader, eventual goal of being able to handle more data.

4. Having a Sound IT Strategy

It is essential for effective, efficient Big Data management. Since your IT framework forms the backbone of all your data processing and management efforts, you need to ensure that your IT strategy addresses two key points:

Ensure that your data management hardware supports real-time governance and control

 Ensure that your IT platform is itself sustainable and scalable for future use

5. Choosing the Best Tech Platform Available

Advancements in the world of data storage, manipulation, processing and management mean that you can choose between a lot of different software, architectures and platforms for every single one of your requirements.

Whether you are using standardized solutions or modified, custom-made best-in-class alternatives, always pay attention to the pros and cons involved. What you need is an efficient, cost-effective and versatile technology platform that can accommodate all your Big Data management needs at present and in the future.

6. Pruning and decluttering your Big Data as soon as you can into the Process

Many companies make the mistake of storing all the data they acquire in their original raw form, in spite of the fact that much of it is likely to never be used. It is a way of playing safe and trying to house as much data as possible in the hope that sometime in future, there might be need of it.

However, there is every chance that parts of this data pool might be unfit for the particular requirements of a business. For example, overhead data generated from internet interactions and network jitter data are also parts of Big Data, but they have no importance in a number of requirement contexts. 

Figuring out parts of the Big Data you work with that you can prune without affecting your expectations and requirements can be a good way to end up with a smaller, yet more relevant and effective data pool, which is both easier and more cost-effective to store and manage.

7. Establishing Governance Standards

Depending on business use cases of Big Data, there should always be a solid, dependable governance system in place which should dictate all procedures concerning your use of Big Data and its management. Governance standards should dictate explicitly who the people with access are, and how much access is granted to them on an individual level.

It should determine if any of the data would be acceptable in a public cloud environment. Standards should also ideally be in place for identifying and better managing data privacy and security issues effectively.

With these seven best practices for Big Data management in the IT sector, you can have a well-oiled, functional, high-performance Big Data management system that can do wonders for your business. Starting from basic data collection to complex forecast calculations and the formation of business strategy in a data-driven way, these practices can always ensure that you get to make the most of Big Data.

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