Big Data Management Challenges Facing Companies and Solution

Big Data Management ChallengeBig data analysis is the process of researching, processing large data sets to discover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. 

Big data does not only revolve around the amount of data the company has, but what is important is how to process internal and external data. 

We can take data from any source and analyze it to find the answers we want in business such as: reducing costs, reducing time, developing new products and optimizing product offerings and making smart decisions.

According to its characteristics, big data can be defined into 5V namely:

  1. Volumes . In the era of IoT ( Internet of Things ), data is generated not only by humans, but also by machines. Human and network interactions in systems such as social media make the data to be analyzed very large.
  2. Variety . Refers to the heterogeneity (diversity) of data sources, both structured and unstructured data . Starting from the form of spreadsheets and databases , until now it is available in the form of emails , photos, videos, audios, and others.
  3. Velocity . Includes the speed at which data moves in, such as from business processes, machines, social media networks, electronic devices, and others. Data flows become very large and continuous.
  4. validity . The data taken must be true and accurate according to what you want to use. Valid data is one of the keys in making the right decision.
  5. Veracity. Refers to data inconsistencies that can occur at any time, thus hindering the processing and management of data effectively.

Here Are The Top 7 Big Data Analysis Challenge Facing Companies

Big Data Management Challenge Facing Companies and Solution
  1. Need to synchronize different data sources. As data sets become larger and more diverse there is a huge challenge to incorporate them into the platform . If this is ignored it creates gaps and leads to the wrong messages and insights .
  2. Lack of professionals who understand big data analysis . With the exponential increase in data, the demand for big data scientists and analysts is growing. It is important for companies to hire a data scientist who has diverse skills because the job of a data scientist is multidisciplinary.
  3. Get important insights through big data analysis. It is very important for the company that only the relevant departments have access to this information. Real-time data can help researchers and companies to provide up-to-date insights for decision making.
  4. Getting voluminous data into a big data platform . Companies need to deal with large amounts of data every day. The amount and variety of data available today can overwhelm data engineers and is critical to making data accessibility easy and convenient for enterprise owners and managers.
  5. Uncertain data management landscape . With the emergence of big data , new technologies and companies, the big challenge faced by companies in big data analysis is to find out which technology is most suitable for them without any new problems and potential risks.
  6. Storage and data quality. Popular data storage options such as data lakes/warehouses are generally used to collect and store large amounts of unstructured and structured data in their original format. Missing data, inconsistent data, logical conflicts, and duplicate data all create data quality challenges.
  7. Data security and privacy. Big data also involves potential risks related to privacy and data security. Big data tools are used for analysis and storage using different data sources. This ultimately leads to a high risk of data exposure and makes it vulnerable. The increasing amount of data also raises privacy and security concerns.

Big Data Management Challenge and Solutions to Overcome Them

In a company, data is produced every minute that comes from business transactions, customers and business partners, and others.

In the modern era, data is likened to fuel to run a company’s wheels so that it reaches its destination through the right choice of route. All data that is owned is collected into a large amount of data which is generally known as Big Data.

Even though data is considered very important for the pace of business growth, the reality is that until now there are still many companies that have not found the right way to manage data to become something of value due to various challenges.

Actually, what are the big data management challenges that often occur in a company? What needs to be done to overcome these challenges? Here’s the explanation!

1. Data From Various Sources Is Stored On Different Platforms

The challenge of managing big data that is common in a company is the need to manage data from various sources, but the data received is stored on different platforms – based on the type of data and the origin of the source. This gap will cause problems during the process of extracting and analyzing data.

If the situation is like that, the analysis of the results of data analysis will tend to be ineffective because the completeness and accuracy need to be questioned.

Aggregating data from various sources manually would be very time-consuming, thereby limiting employees’ vision of “ insights ” that should be visible easily.

The solution to addressing the challenge of managing big data is to use a big data analytics platform that is comprehensive and capable of centralizing data in one centralized location – regardless of the type of data and where it comes from.

2. Classifying Quality Data

With so much data owned, it will be difficult for employees to classify quality data. In the end, the analysis process does not focus on data that really has value for the progress of the company’s business.

In addition, if employees have to classify quality data manually, then they will not get real-time data to find the latest trends.

The inability to view data in real-time will have many significant negative impacts on the quality of decisions made based on available data or what are commonly called data-driven decisions .

Big data analytics solutions equipped with artificial intelligence (AI) and machine learning capabilities will help companies overcome the challenges of managing big data. 

AI and machine learning support  can help employees classify quality data for automatic analysis, so that analysis results can be better, faster, more accurate and in line with current trends .

3. Lack Of Employees Who Have The Ability To Analyze Data

Even though times are getting more advanced and modern, in reality there are still many companies that do not have a sufficient number of employees to analyze data properly. This problem occurs because the operation of the platform is complex, only certain employees can be relied upon to analyze data.

If the situation is like this, it will be difficult for companies to keep up with the pace of business competition development, because the data analysis process takes a very long time.

The solution to addressing the big data management challenge is to use a big data analytics platform that helps each employee access and utilize available data without having to learn complex tools or programming languages ​​to operate.

4. Requires A Lot Of Money

The next big data management challenge is the large amount of money required to run an effective data analysis process. To overcome the challenge of managing big data, companies can implement a big data analytics platform that offers flexibility in terms of payment schemes. 

By choosing a big data analytics platform that offers flexible payment schemes, companies only need to pay according to the features they need and use. Thus, companies can incur more efficient big data technology investment costs.

5. Scalability Issues

Along with the development of the company’s business, the amount of data that will be produced will be more and more uncontrollable.

The increasing amount of data will cause new problems in data storage and management, because the process will be more complex. Many companies fail to manage their data effectively as their business grows. 

The big data analytics platform that has been used since the beginning did not have the ability to manage an increasing amount of data.

To overcome the challenge of managing big data, companies need to use a big data analytics platform that offers scalability – that is, having the ability to manage unlimited amounts of data without affecting the quality of the analysis. 

So, companies don’t need to worry about the need to manage big data which is increasingly complex if the business is growing.

This is an explanation of the challenges of managing big data and solutions to overcome them. If your company is experiencing these challenges, then implementing the Teradata Vantage big data analytics platform will be the right solution for you.

The Teradata Vantage big data analytics platform is a data processing platform capable of aggregating and analyzing various types of data from several different sources. 

In addition, this platform comes with capabilities and benefits that are able to overcome all the challenges of managing big data – a platform with good scalability capabilities, analysis results supported by AI and machine learning, a “ pay as you go ” payment scheme, and enables all employees to perform data analysis without special skills, because anyone can do the operation without having to learn complex tools or programming languages.

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