Big data management is a critical aspect of modern business operations. In today’s digital age, the sheer volume of data generated on a daily basis can be overwhelming for businesses of all sizes. From customer transactions to social media interactions, every aspect of a company’s operations can generate valuable data that can be used to make better decisions.
Big data management is a process that involves the collection, storage and analysis of large amounts of data. It is often used by organizations to extract insights from the data in order to make decisions that are more accurate and make better business decisions.
The importance of big data management has increased with the availability of more sophisticated components and technology tools which can handle large amounts of information. Businesses are doing their best to stay up to date with big data trends to gain competitive edge.
An example is using business intelligence tools to collect all company’s internal data and then analyze it for insights about customer behavior or potential opportunities.
In this article, we’ll explore what big data management is, why it’s important, and how businesses can benefit from it. So, let’s dive into the exciting world of BDM!
Over the next five years up to 2025, global data creation is projected to grow to more than 180 zettabytes.source: Statista
What is the importance of big data management (BDM)?
The importance of big data management is that it provides businesses with a competitive edge in the digital age. It enables them to understand their customers better and provide them with more personalized services.
Here are the top benefits of BDM:
1- Higher revenue
When data is effectively managed, organizations experience a substantial boost in their revenue streams. Proper big data management leads to improved data quality solutions, which, in turn, result in significant revenue growth and enhanced financial performance.
In addition, it has the ability to enable organizations to cover untapped revenue streams that were hard to find.
2- Improved decision making
By effectively harnessing and analyzing vast volumes of structured and unstructured data, organizations can gain valuable insights and a comprehensive understanding of their operations, customers, and market trends.
This valuable information, if properly managed, will enable data-driven decision making and ensure that your higher management has the methods to make decisions based on concrete evidence rather than intuition and estimates.
Additionally, it allows for real-time monitoring and analysis, enabling organizations to respond promptly to emerging disruptions and capitalize on untapped opportunities.
3- Accurate analytics
BDM provides a solid foundation for data processing, storage and retrieval. The high volume, velocity, and variety of data generated and collected can be overwhelming but with effective big data management strategies, businesses will be able to handle data in a way that will allow them to get the most out of it.
It fosters scalability and flexibility, ensuring that analytics platforms can handle the ever-expanding data volume and adapt to changing analytical needs. By combining efficient data with advanced analytical tools, organizations can derive valuable insights, identify patterns, and make data-driven decisions that drive innovation, optimize processes, and ultimately lead to sustainable success.
4- Minimized data loss
The best approach to have a successful big data implementation is to include robust backup and disaster recovery procedures, where data is regularly backed up and stored redundantly across different locations or cloud services. These backups serve as insurance against data loss, allowing for swift recovery in case of any unforeseen incidents.
The main goal for organizations should be having the ability to mitigate the risk of data loss, protect critical assets, and maintain uninterrupted business operations.
5- Improved compliance
Effective big data management will ensure that organizations adhere to the required data governance standards and privacy laws. Many industries, such as healthcare, finance, and telecommunications, are subject to strict regulations concerning the handling, storage, and sharing of data.
It involves implementing comprehensive data governance frameworks that define clear policies and procedures for data handling, storage, and access. These frameworks help organizations maintain data accuracy, integrity, and confidentiality, which are essential components of regulatory compliance.
6- Improved organizational efficiency
Managing big data can improve organizational efficiency by reducing the amount of time spent searching for data, improving data quality, and making data more accessible to employees.
By optimizing data-related processes, empowering data-driven decision-making, and streamlining operations, organizations will be able to provide higher and more efficient operational workflows that will better serve customers.
What are the challenges faced during the implementation phase?
Here we look at the significant obstacles that organizations will mostly face during big data management implementation:
1- Data silos
Having different data repositories across your organization will make it harder to consolidate it in one platform that will allow you to slice and dice it to identify patterns and make better decisions.
Like we always say to our clients, the less the repositories the better the analytics.
2- Data storage
As data continues to grow, it will become harder to manage the infrastructure and scale up and down accordingly. That is why most organizations are migrating to the cloud for better scalability and more cost effective.
3- Data variety
With the advancement of technology, we are generating tons of data in different formats. Organizations should identify the types of data that they are dealing with and create the perfect strategy to handle it propery.
In case you are interested in knowing more about this subject, check out this in-depth guide “Big data challenges“
What are the most common BDM Best Practices?
Successful BDM paves the way for analytics projects that may aid businesses in making better business decisions and strategic planning. To set big data initiatives on the correct track, use this list of recommended practices:
1- Know what data is important and what it is not
Not every generated data should be stored and used in your operational flows. Organizations should only keep high quality and important data will is needed for the quality of decisions and gaining insights more about the daily business.
2- Simplify backup methods
You need to make sure that data stored is always being backed up in order to prevent data loss and recover it in case of natural disasters.
3- Implement high data security measures
In today’s interconnected world, data breaches and cyber-attacks are on the rise, posing significant threats to organizations of all sizes and industries. High data security measures help safeguard critical data from unauthorized access, theft, or malicious intent.
By implementing robust encryption techniques, access controls, and multi-factor authentication, organizations can ensure that only authorized personnel can access and manipulate sensitive data.
What are the components of big data management?
Big data management encompasses a range of processes and tools that enable businesses to collect, store, process, and analyze large volumes of data. These components include data acquisition, data storage, data processing, data analysis, data governance, and data quality management.
Understanding how big data management works and how businesses can put up the most effective policies and procedures to get the most out of it is the key to unlocking the potential of data as a driver for organizational success.