Big Data Software

What is big data software?

Big data software manages, stores, and processes large volumes of data. The tool helps businesses analyze unstructured datasets from a large pool of data to draw meaningful insights. 

Big data software typically offers features such as real-time reporting capabilities for faster decision-making, predictive analytics algorithms for identifying trends in customer behavior or market movements, and scalability options that allow increased storage capacity. Additionally, many big data solutions offer visualization tools to create comprehensive yet understandable reports on performance metrics.

What are some common features of big data software?

• High volume data processing: Process vast volumes of structured or unstructured information in real time, allowing informed decision-making. 

• Data mining: Analyze large amounts of data and uncover useful trends, patterns, correlations, and relationships. 

• Data cleansing: Detect and fix errors in data sets, ensuring the accuracy of information 

• Data blends: Simplify the process of combining data from multiple sources, such as databases and spreadsheets. 

• Data visualization: Visualize complex data sets by creating charts, graphs, diagrams, and other graphic representations. 

• Data warehousing: Store and manage large amounts of data, allowing teams to access the information they need with role-based access quickly. 

• Predictive analytics: Identify patterns, trends, correlations, or relationships that can be leveraged for predicting future outcomes and optimizing decision-making.

What are the benefits of using big data software?

• Automate data analysis: Using big data software, you can automate data analysis and get valuable insights into your business’s performance. The tool simplifies collecting, organizing, analyzing, and visualizing large amounts of information to uncover hidden trends or patterns in your business operations. This saves time by eliminating manual tasks associated with traditional analytics processes so you can focus on framing future growth strategies.

• Enhance data collection: Big data software lets you collect, organize and store large amounts of structured or unstructured datasets. You can gain deeper insights into business operations with access to real-time analytics, predictive modeling, and more accurate forecasting capabilities. 

• Enable data-driven decision-making: With big data software, you can analyze and interpret large amounts of structured or unstructured data quickly and accurately, identifying trends in customer behavior, market opportunities, cost savings insights, and more. With real-time analytics capabilities, you can make decisions that positively impact the bottom-line results and overall business performance.

• Increase data security: Big data software provides a secure platform to store, analyze and share business data. The tool further prevents unauthorized access and protects the integrity of your sensitive information by encrypting it at rest or in transit. Additionally, the advanced security features let you monitor user activity so that you can quickly detect any suspicious behavior before confidential records are compromised.

• Allow data visualization: You can use big data software to make complex datasets easier to understand and provide insight into trends, correlations, and patterns that may not be visible otherwise. Visualization tools such as charts and graphs let you identify relationships between different variables in the dataset while providing an overall picture of how those variables interact over time.

What are the potential issues with big data software?

• Difficult to manage the database: Big data software can be difficult to manage due to the size and complexity of datasets. The amount of data processed is often larger than traditional databases, requiring extra resources for storage and processing. Additionally, understanding big data requires specialized skills that may not always be available or affordable for your business. As a result, managing large amounts of big data effectively can prove challenging without the proper knowledge and technology in place.

• Poor data quality: Poorly collected or stored information can lead to inaccurate analysis and results, making the system unreliable for decision-making. This may also lead to wrong decisions based on outdated knowledge, disrupting the business strategy and growth. 

• Data security and privacy issues: Unsecured systems can lead to unauthorized access or misuse, while inadequate user access management may increase the risk of identity theft and fraud. Furthermore, you must be aware that legal regulations (General Data Protection Regulation - GDPR) require you to protect any personal data collected from customers.

• Inaccurate analysis and insights: Without accurate information, businesses may make poor decisions, leading to costly mistakes. Furthermore, inaccurate analyses can also cause distrust from stakeholders who rely on the accuracy of these reports for making business decisions. This lack of trust in the data or its interpretation has long-term negative impacts on your business’s reputation.

How much does big data software cost?

Most big data software products are priced on a “per month” basis, and their entry-level pricing plan ranges from $19 to $1,000+* per month. An enterprise product that’s priced higher may include additional features such as user groups, activity logs, and advanced data preparation.

*The pricing included is for the entry-level/lowest-priced offerings found on vendor websites as of March 17, 2023. 

Key considerations when purchasing big data software

• Check the platform’s scalability: Scalable solutions make room for future growth in data size and complexity without disruption or extra costs. Additionally, they allow you to tailor the data storage solution as needed while managing a larger database efficiently with fewer resources. Scalability allows for greater flexibility and cost savings when incorporating new technologies or expanding operations, ensuring a smooth transition as more customers are added or services grow in demand. 

• Evaluate the range of analytics features: Ensure the software provides a comprehensive set of analytical tools and capabilities to enable advanced data analysis, including predictive models, machine learning algorithms, time-series forecasting, etc. Additionally, consider if there are any specialized analytic functions available, such as natural language processing (NLP) or customer segmentation, which could be beneficial in complex scenarios.

• Assess the data processing speed: Faster speeds allow for quicker analysis and more rapid insights into the large volumes of data, improving efficiency in operations and decision-making processes for your business. Ensure that the software provides a comprehensive set of analytical tools and capabilities to enable advanced data analysis including predictive models, machine learning algorithms, time-series forecasting, etc.

Sources

Products evaluated for the pricing calculation were taken from GetApp’s big data software directory, sorted by the number of reviews. The pricing ranges exclude freemium versions of the products. The features highlighted were identified based on their relevance and the percentage of products in GetApp’s directory that offer them. 

Disclaimer

This big data software buyers guide was authored by GetApp’s content team. We develop our guides using the author’s expertise, insights from 2M+ unique user reviews, and our proprietary data science algorithms to identify trends in user sentiment, preferences, and priorities. Some text was generated with assistance from AI tools.