Big Data first appeared in 1997 in a NASA scientific paper to describe large, diverse, and complex amounts of data. When discussing Big Data, there are two main focuses: how this data can improve business performance, and the challenges of implementing it in the era of digital transformation.
In the following article, learn more about the challenges of Big Data implementation and the right solutions to overcome them.
Definition of Big Data
Big Data refers to large and complex data sets that come from different sources and types. The data in Big Data is generated rapidly and continues to grow at a high rate. The sources of this data can vary from sensors, IoT devices to social media. In addition to structured data such as numbers in spreadsheets, it can also be unstructured data like emails, social media messages, photos, and videos.
The variety of these data types makes them difficult to manage, and the sheer volume of data is a challenge. Big Data can generally reach a very large size, reaching terabytes, petabytes, and even exabytes. No doubt, its management becomes difficult when using traditional methods.
3 Big Data Functionalities
Big Data plays an important role in many aspects of modern business and technology, particularly in three key functions that have a significant impact on decision making and operational performance.
Analysis
Analyzing data on a large and complex scale helps identify patterns, trends, and insights hidden in the data. This enables organizations to make smarter and more strategic decisions by uncovering valuable information such as customer preferences, buying patterns, or operational efficiencies.
Prediction
Big Data enables trend forecasting based on historical data analysis, resulting in more accurate predictions of what might happen in the future. For example, predicting market demand, price fluctuations, or inventory needs. This allows companies to take appropriate actions, anticipate changes, and optimize strategies.
Optimization
Big Data opens opportunities to improve operational efficiency and reduce costs by using data to understand how business operations are running. This allows companies to identify areas for improvement, such as optimizing the supply chain, reducing waste, or improving resource utilization.
Big Data vs. Conventional Data
Conventional data generally has a small volume, a clean structure, and can be easily processed using conventional tools, such as sales data, customer data, and financial transaction data. This type of data can be easily analyzed using statistics and conventional data analysis methods.
On the other hand, Big Data is very large, unstructured, and complex. Examples include social media data, IoT sensor data, and scientific research data. This data is difficult to process with traditional tools due to its large volume and diverse formats. Analyzing Big Data requires specialized techniques and infrastructure.
To differentiate it from conventional data, Big Data has the following unique characteristics:
- Volume: Big Data has a much larger volume and continues to grow rapidly.
- Variety: Big Data comes in a variety of formats, including text, images, video, and sensors.
- Velocity: Big Data is generated and processed at high speeds.
- Accuracy: The accuracy and consistency of Big Data must be maintained to make it trustworthy and useful.
Big Data Implementation Challenges
While Big Data promises many benefits, its implementation also comes with some significant challenges that must be overcome. Here are some common challenges in Big Data implementation.
Infrastructure
Storing and processing Big Data requires a robust and scalable infrastructure, including high-capacity hardware, fast networks, and specialized software. The cost of building and maintaining this infrastructure can be prohibitive for many businesses.
Skills and People
Managing Big Data requires specialized skills, such as data scientists, data engineers, and data analysts. The availability of people with these skills is still limited, making it a challenge to run Big Data.
Data Quality
Inaccurate, incomplete, or inconsistent data can lead to faulty analysis and wrong business decisions. Cleaning and managing data quality in large volumes is a challenge.
Data Security
As the volume of data stored increases, so does the risk of data leakage and security breaches. Businesses must implement appropriate security measures to protect sensitive data and comply with data privacy regulations.
Data Integration
Big Data often comes from a variety of different sources, so integrating and unifying these disparate data sources becomes a challenge to perform thorough analysis.
Data Analysis
The analysis process requires specialized tools and techniques. Businesses need the tools and expertise to manage and analyze these large volumes of data efficiently and effectively.
Despite the challenges, with careful planning, proper investment, and effective strategy implementation, businesses can overcome these challenges and reap the benefits of big data. One solution that can help address these challenges is provided by Hitachi Vantara’s Hitachi Data Protection Suite. How can it help you? Let’s find out.
Efficiently Protect and Manage Big Data with Hitachi Data Protection Suite
In the age of Big Data, businesses are looking to maximize the value of their data, and one increasingly popular solution is the use of object-based storage. Compared to traditional file and block storage approaches, object storage offers several advantages, including lower costs, easy capacity expansion, and easier data access and management.
Hitachi Vantara introduced Hitachi Data Protection Suite (HDPS) as a unified, modern solution for backup, recovery and management of enterprise and application data. The solution is powered by the Hitachi Content Platform (HCP), the industry’s leading object storage platform.
Best Features of HDPS and HCP
- Reliability and Security: Meets the reliability standards required by large enterprises, with security features to protect critical data from internal and external threats.
- Convenience and Cost-Effectiveness: Simplify data management with seamless integration between HDPS and HCP, reducing costs compared to using separate solutions.
- High Capacity: Large storage capacity capable of storing petabytes of data for long-term retention.
Benefits of Using HDPS and HCP
- Efficient Data Protection, Management, and Recovery: Easily protect, manage, and access data through a unified interface.
- Fast Data Recovery: Recover the data you need in minutes or hours.
- Improve Data Protection and Management: Optimize costs and automatically backup data to the Hitachi Content Platform without disrupting data access.
- Simplify Administration: Reduce administrative training time and costs by increasing capacity utilization and reducing data backups by 36 percent.
- Protect and Retain Data at Scale: Manage data protection and retention for tens of thousands of users from a single, easy-to-manage platform.
- Manage All Enterprise Data: Protect and manage data from multiple sources, including virtual and physical servers, applications, snapshots, replication, cloud infrastructure, and mobile devices.
- Secure, Flexible, and Affordable Storage: HCP provides a highly scalable, long-term cloud object storage platform with strong security features.
- Reduced Backup Burden: Provides fifteen 9’s data resiliency, erasure coding, replication, configurable redundancy, and automatic repair and versioning.
Get Hitachi Data Protection Suite from CDT
Efficiently manage and strengthen your Big Data strategy with Hitachi Data Protection Suite (HDPS) from Hitachi Vantara at Central Data Technology (CDT). As Hitachi Vantara’s authorized partner in Indonesia, CDT can help you to recommend Big Data management strategies according to your business needs.
Supported by a professional, experienced and certified IT team, CDT will also help you through the stages of consulting, deployment, management and after-sales support to avoid trial and error when implementing Hitachi Data Protection Suite (HDPS).
Discuss your business needs with us by clicking this link.
Author: Wilsa Azmalia Putri
Content Writer CTI Group
