Big Data analytics allows you to dig deep into large amounts of data to uncover hidden patterns, data connections, or other useful insights that can help your company discover new opportunities.

Big data analytics can help you make better business decisions, improve customer satisfaction, and increase profits by harnessing your information. 

Without the right equipment, however, you will have to sort through truckloads and process them for their value. This can take many years.

There are many tools available today to help you analyze and collect big data.

This post will discuss the top tools for big data analytics that can make a profit.

Big Data Analytics Features and Benefits

Here are some benefits that Big Data analytics can bring to your business before you dive into it.

• This tool will help you better understand your customers and users.

• Discover insights that will help you provide better service to your customers.

• Find previously overlooked opportunities to improve your business processes and enhance your approach

• This will help you to reduce fraudulent activity that could affect your business.

Understanding the benefits of big data analytics will help you to determine the type of tools that your company needs.

Let’s take a look at the factors you need to consider when selecting the right data analytics software for your company. The tool that uses AI- Our future technology for nearly all industries.

• Import and export of data. Keep in mind that you will be dealing with a lot of information. Your software should make it easy to import and export data.

You should choose a tool that can connect to your big data storage and your analytics tool, such as for example.

• Integration. Integration.

• Analytic Capabilities. You should verify that the tool you’re considering using offers multiple analytics capabilities with different models to perform different types of analysis.

These include decision trees, neural networks, predictive mining and time series.

• Collaboration. Although analysis is often a single activity, it can sometimes involve some collaboration to achieve better results.

• Scalability. Big Data will continue to grow in importance. This means that you must understand and consider the possibilities for scaling your analytics tools.

• Visualization. Visualization is a great way to visualize numbers and figures. However, visualizing data in other formats like graphs and charts can make it easier to understand.

You can learn the skills, strategies and tools needed to successfully use Big Data analytics to increase your profits by enrolling in an Big Data Hadoop online certificate training course

It is important to be familiar with the various tools available and how they can be used for Big Data analytics. This will help you improve your business.

Interacting with the tools can provide you with a first-hand view of how data is processed and analyzed to give you actionable results.

6 useful tools for Big data analysis

1. KNIME

Konstanz Information Miner is an open-source program that can be used for enterprise research, integration and business intelligence. It also allows you to report, text mine, and CRM.

The tool’s analytics platform allows you to build data science visual workflows without having to code.

You can also combine data from all sources, create statistics, sort and aggregate information, or even build machine-learning models.

KNIME also helps you validate and make predictions based upon your models, store processed data and scale your workflow performance with multi-threaded data processing or in-memory streaming.

KNIME’s easy-to-use features will give you a large algorithm set and lower stability chances. It also automates many of the Big Data analytics manual tasks.

This will help you to design your data science workflows faster and more efficiently.

2. MongoDB

MongoDB may be the right solution if you have trouble managing your Big Data databases.

MongoDB, a cloud-based document-oriented, general-purpose open-source database management software, is made for the Cloud. It supports multiple data types and uses a document-oriented structure.

To accommodate more data types than the common column or row model, the tool’s structure is made up of JavaScript Object Notation JSON (JSON) files and collections.

MongoDB’s rich JSON documents will allow you to work more naturally with data, as it supports dynamic and flexible schemes.

Expressionistic and rich query languages allow you to sort and filter by any field regardless of its embeddedness within a document.

You can also access the capabilities and functionality of a relational data base using two types (embedded or reference) of relationships instead of just one.

MongoDB is your data platform. You will have an extensive suite of tools to make managing your database and working in Big Data easier and more enjoyable.

3. Octoparse

Data extraction can take up a lot of your time and energy. Additionally, it may require certain skills such as coding in order to obtain all the information you need.

With an intuitive web scraper such as Octoparse you can quickly extract data from web pages and convert them into structured spreadsheets in a matter of seconds, and without any coding.

These are the main features Octoparse has to offer.

• Cloud Extraction. Cloud Platform allows data extraction to be performed 24/7. It can extract data up to six times faster than traditional methods. The data is available in the Cloud and can be accessed from any device.

• Schedule Extraction. Cloud Extraction allows you to schedule tasks for a specific time each day, weekly or monthly. This makes it possible to extract new data from websites that are updated regularly.

• Point-and-click interface. This tool employs an advanced machine-learning algorithm to pinpoint data as soon as you click it.

Simply open a website using the built-in browser. Click on any web data that you wish to extract and then click and drag them to begin a scraping job.

• You can deal with different types of websites. Do not let the complexity of a website’s AJAX, JavaScript or other dynamic websites intimidate you.

You can use scraping to extract data from fill-in forms. Click through endless scrolls, switch drop down, and logins. Then, you can get any information from web pages like links, HTML codes and more.

These data extraction tools allow you to track prices and get competitor data. This will help you build your sales list and improve your lead generation strategies .

Web data can be extracted to boost marketing strategies, make better predictions and make better decisions. You can also get data for research data models.

4. Semantria

Data collection is not as simple as it appears.

Unstructured text, such as instant messages and emails, or social media posts, cannot be easily mapped into standard database fields. This makes it harder to mine and process.

You can make your social media data collection more efficient by using a platform that helps you store, manage and analyze unstructured texts such as Semantria.

This tool allows you to store and manage text documents. It connects your databases and processes and manages text documents from multiple sources.

Semantria can also convert your unstructured text to structured data by natural language processing. It extracts data points from topics, categories, intentions, and topic groups.

After extracting these data points, this tool assigns multi-layered sentiment ratings. This gives you insight on common topics, how people feel and why.

Your analytics dashboard can be customized to show patterns and trends in the most popular topics as well as how people feel about these topics.

Semantria makes it easy to collect unstructured data on social media. This will help you understand your customers’ attitudes toward your brand.

It allows you to drill down on patterns and trends, better understand your customers, and make data-based business decisions that will bring you profit.

5. Qubole

Big Data can present a challenge in transforming all the information into actionable insights.

This is a great way to solve this problem. Make your data accessible across all usage points. Users can access the data they need and activate critical mass.

This will help you bridge the Big Data activation Gap, or the gap between the supply and use of data.

Qubole is a useful tool in this situation.

Qubole makes use of a Cloud-native platform that allows you to activate petabytes more quickly.

Other Big Data analytics features of the software include:

• Multiple data processing engines. You can choose the right tool to do the job with the various engines available, including Spark, Tensorflow and Hive.

• Development benches. You can quickly write code using various interfaces and workbenches, including command line, dashboards API, notebooks, and API.

• Automated cluster management. Automated cluster management. The tool will shut down clusters without exposing data loss if there are no active jobs.

You can save money on Cloud compute costs by only paying for actual compute usage.

Qubole, a tool that helps you solve the Big Data activation problem, offers features that allow you to expand data users, variety and use cases.

It also offers reliability, cost-effectiveness, and responsiveness benefits for applications that process large data sets.

6. Tableau

If you are new to Big Data analytics, it can be confusing and overwhelming to see and understand large amounts of data.

Tableau is a great tool to help you quickly and easily analyze and explore data.

This analytics platform allows you to drag and drop data sets to be analyzed for trends or outliers. Natural language can also be used to explore the data.

Connect to the data you need, from your spreadsheets, Big Data, data warehouses or Cloud data. You can also combine data from different sources to perform analysis.

Smart grouping algorithms make it simple to organize your data.

After you have organized your data, you will be able to publish your flows and schedule them with the prep conductor.

The tool’s visual interface allows you to ask questions, alter your data analysis perspective and uncover deeper meanings. It also lets you transform your data into powerful dashboards that are interactive and powerful.

Online sharing of data and dashboards is possible through fully hosted solutions like Tableau online. You can also manage your server at home or on the Cloud.

You can publish through these channels to allow everyone in your company access to your data and dashboards, allowing them to uncover their own insights.

Tableau’s data management tools will give you complete control over all aspects of your data, from user permissions to data source connectivity. You also have the visibility that you need to support data deployment.

Last Thoughts

Although you can access and collect truckloads upon truckloads of data you will not be able to turn them into the valuable information your business requires.

You have many options for Big Data analytics tools, but these are the best six to get you started.

You might need to do some trial and error before you find the right tools for your business. But it is worth the effort.