The world is surrounded by data in a literal sense. Many businesses today rely on data to develop products and services to ensure success and continuity. Simple data is manageable as it can be easily stored, analyzed, and presented on spreadsheets, etc. But, when considering big data handling, things are often all over the place.  

Extracting and analyzing data from such massive amounts is difficult, especially with conventional data handling tools, let alone using big data as an asset to drive business growth. Additionally, the technology for handling the data costs more to most startups.  

So, what's the best way to effectively manage such massive amounts of data to make the best of them? It's through data management strategy. By implementing such a strategy, you can avoid the most significant data challenges like inconsistent, incomplete, duplicate, and missing data but ensure consistent data management and business growth.  

Here's sharing the five simple steps to set up successful big data management to help you make the most from the data asset.  

Outline Your Business Objective:  

As a business, your organization creates massive amounts of data every day. And if your business objective isn't in alignment with your data management strategy, you could be losing valuable time and resources collecting, storing, and analyzing the inessential data. Hence you must focus on what, as a business, you want to achieve now and in the future. The following questions will help you identify the answer.  

• What are your business's overall objectives? 
• What data do you need to realize those objectives?  
• What information and insights are required to get started?  

Identify the top 2-3 use cases from your business data and create a strategy around them. Once you are clear of your objective, you can determine the rest of the process.  

Streamline Your Data Process: 

Now that you know how you want to use your data, it is time to set up a defined process for collecting, preparing, storing, and analyzing data. Start by identifying the owner for each of the big data management processes. Here are a few essential steps to follow:  
 

Data Collection:  

• Identify your data sources  
• Take into consideration your internal and external assets.  
• Based on your needs, look for structure, in structures, and combination data.  
• Plan the data collection process.  
• Extract data either manually or set up an automatic extractor. 

Data Preparation:  

• Clean the raw data for analysis  
• Identify the errors in the data  
• Set up guidelines for data to increase discovery ability, like data name, metadata, etc.  

Data Storage:  

• Spare a dedicated storage space for data  
• Use XML, CSV, or relational databases for storing structural data  
• Consider a centralized repository data lake) for unstructured data. 

• Take proper security measures.  
   

Data Analyzation & Distribution:  

• Identify the team and department that requires collaboration  
• Find ways to ease the data access  
• Identify the ways to communicate data insights.  

Employ the Right Tools for Big Data Management:  

Once you are clear about the above steps, you will need the right tools & platform to execute your big data management strategy. Consider your hardware and software are required to establish a robust data infrastructure. Employ data management add-ons for managing data within the analytics environment and streamline the process to ensure data availability. These add-ons help from data preparation to classifying to governance, ensuring you have up-to-date data to drive meaningful business decisions.  

Setting Up Data Governance is Essential:  

To effectively manage data is a big responsibility. Hence establishing data governance is crucial. It ensures that your data is used authentically across the organization. Spend some time outlining and communicating proper standards and policies for data usage to stakeholders and employees. 
 

Some of the aspects of data governance are: 

• Data Quality: Ensuring data is correct, complete, and up to date. 
• Data Security: Outlining the steps to store data securely. 
• Data Privacy: Permission for data collection and usage.  

• Data Transparency: Fostering an ethical data environment.  

Train to Execute:  

The biggest challenge comes from big data management & its utilization comes from inexperience. But one of the integrals of data management is how efficiently you analyze and understand the underlying data. Hence, it's essential to focus on this aspect. It could mean putting data analysis tools & required skills in the hands of your team or department or outsourcing it. But whatever your choice may be, make sure everyone knows your company's data management strategy and how to manage their part successfully. 

Wrapping Up:  

Knowing how big data management works can help businesses plan out the most effective strategies, procedures, and practices to unlock the enormous potential of data as an asset. And it's an integral component for driving the organization to success.