According to data by Statista, the global market for big data will be worth $103 billion by 2027. This is because businesses in all sectors now have access to huge volumes of data. However, despite this access, business managers require a set of tools, technologies and proper data management systems to get the most value out of this massive amount of data.
Proper big data management helps businesses and their employees make better decisions, protect company stakeholders and boost the company’s profitability. It comes in handy when managing huge volumes of structured and unstructured data from various sources and using it for the benefit of the business.
Therefore, if you are looking to integrate big data into your business, this article will provide you data management tips to get you started.
Data management refers to the process of collecting, keeping, organizing and protecting data. Once a company gets data from different sources, they manage it effectively and gain insights for business decision making. When you are dealing with big data, you need a strong data management strategy that involves data processing, data governance, data security and data storage to streamline company operations.
Organizations that use data management initiatives get benefits, such as reduced data silos, enhanced customer experience, improved security and compliance and business scalability.
Big data refers to the huge amounts of unstructured and structured data that businesses collect to drive better decisions and strategies. Managing this huge set of data can be complex for most organizations that still use traditional data management tools.
Social media platforms and stock exchanges are examples of big data because they generate terabytes of new data every day. Big data is important to business because it improves operations, helps create personalized campaigns and improves customer experience. For instance, a business can use big data to study purchasing behaviors and use this real-time data to tailor their marketing campaigns. Also, big data comes in handy in predictive modeling and machine learning.
Over the last decade, technology has advanced in areas like artificial intelligence, cloud systems and Internet of Things (IoT), leading to the exponential growth of big data.
For this reason, it has become necessary for businesses to integrate it in the core areas of the company to compete against players in the industry. Additionally, big data brings in more business opportunities because managers can make faster and more informed decisions. So, how can companies integrate big data into the processes? Here are some tips.
As said earlier, big data can be structured, or unstructured. Structured data is in a fixed format that can be easily understood, while unstructured data is a combination of text files, images, and videos in raw form. For both sources of data, you need to watch out for poor data entry, errors, and bugs that affect the accuracy.
To adopt big data into your business, your data management process should be transparent. For instance, if you are collecting customer feedback online or sales numbers from different sources, you need to confirm the accuracy of the data before moving to the next step.
You can incorporate a smart collection process and hire a skilled team to ensure that the integrity is maintained. With the right team and systems, you avoid using the wrong data that may negatively impact the decision making process.
Data security involves protecting your data from unauthorized use to avoid corruption or leaks. If the data is corrupted, it becomes inaccurate, unusable and unreadable; therefore, it can’t be used for decision making. To integrate big data into your business, you need to keep all the information safe from hackers by adding access controls, authentication layers, encryption and backup.
Your data security should cover hardware, software, backups, user devices, storage, admin controls, access and data governance. For instance, if you are operating a financial institution, you need big data to conduct real-time market analysis. For the process to be effective, you also need to protect customer and business financial information that’s coming in from different sources. You can do this by adding features like permission controls and firewalls that will protect the data.
An important part of data security is using a data access platform to enable common data security policies to apply across all your data. These include giving access to data according to roles (RBAC) and attributes (ABAC), giving temporary access to sensitive data, and dynamically anonymizing data per specific security, privacy, compliance and governance requirements.
Due to the magnitude of big data and the ever changing technology trends, your business needs to keep up. With so much data to analyze and sort through, it’s not easy to execute this manually. Traditional data management tools like Excel sheets will become unsustainable after a while; you need data management software that can handle a huge amount of data.
There are different data management softwares in the market. Statistics show that the Enterprise Data Management market size was valued at $77.5 billion in 2021 and is projected to reach $130.6 billion by 2028. The market is growing due to the demand for such software by both small businesses and large enterprises.
Therefore, if you want to integrate big data into your business, you need to choose the ideal data management software depending on the size of your business. For instance, there are options like Oracle, SAP, IBM, Zapier, OneDrive and Azure that come with different features. Take time to find a reliable and affordable solution for your business to enjoy the full benefits of big data.
In the business environment, virtually every system collects data from different sources. Most of this data can be used for future predictions. Big data brings in a wealth of insights into customer behavior and industry dynamics. However, it also comes with challenges such as security risks, data silos and decision making bottlenecks.
Business teams and leaders that can address these challenges succeed in integrating big data. In addition, this empowers data science teams to leverage more advanced analytical tools like machine learning to enable informed business decisions.
Article Contributed by Ben Herzberg is the Chief Scientist of Satori