5 Big Data Analytics tools [2020]

Data is driving 2020 and will continue to do so in the times to come. You will see the growth in the use of data, and thereby there is going to be a demand for big data experts who can analyze this data and derive useful solutions. Whether we use mobile phones, laptops, or even the infotainment systems, everything is driven data. With the burgeoning increase in this, there is also a steady rise in the demand for professionals who have big data analytics certification. This skilled workforce is actually responsible for deriving useful information from the scattered data. 

So, how do big data experts work? Well, they have a set of tools and software that will eventually help them aptly analyze and derive useful information from it. Well, this information is useful for companies. In this blog, we will be unveiling five such useful big analytics tools that you must learn as a part of your big data online training, but before that, let's have a quick look at some statistics.

• Around 1.2 trillion searches are made every year on Google.

• Facebook users and send more than 31 million messages 

• American companies spent more than $57 billion in 2017 for gathering data.

• In 2012, Gartner forecasted that big data would give rise to 6 million jobs in 2015, and practice these numbers outgrew what Gartner had predicted.

• 5 exabytes of information was created from the start till 2003, and now this much data is created in 2 days globally. 

With these glimmering figures, we can say that data is surely an obsession that is gripping every company, and at the same time, it is also paving the way for new developments. But this data is scattered, and for it to be useful, it is important to filter and scan it. This is where Big Data comes into the picture. Big Data Analytics is a hot topic of discussion for many, and several tools are simplifying the task for big data experts. 

Big Data Analytics Tools that you need to learn in 2020:

1. Xplenty: One of the first tools that you need to learn in Xplenty. This provides a solution based on the cloud. This is an easy to use platform which allows easy cleansing of data. While doing so, it adheres to stringent compliance policies. 

Key features:

1. It is a code-free data transforming and cleaning tool

2. Flexibility in sending data to database, salesforce and data warehouse

3. You can easily pull data from any source

4. Higher security. The encryption offered by Xplenty is because it matches strict compliance policies

5. Customer-centric with round the clock customer support

2. Skytree- If you want a tool that offers accurate results, then this is the right tool for you. It provides accurate machine learning models. Moreover, it is easy to use, then you must consider using Skytree. This

Key features:

1. Offers scalable algorithm

2. AI for data scientists

3. It enables the data scientists to envisage and what works behind the scene of every ML decision 

4. It is easy to adopt GUI

5. Model interpretability

6. GUI access

7. Written in Java

3. Splice Machine- It is also a  big data analytical tool. The tool is portable and can be used across public clouds like Azure, Google, AWS.

Key features:

1. Highly scalable 

2. This is an automated tool which can quickly evaluate every query 

3. Lesser risk

4. Faster deployment

5. Ensures faster determining of data and deploys of advanced machine learning models 

4. Elasticsearch-  This tool is used for solving a number of use cases, this works on JSON-based big data search engines. It offers maximum reliability, horizontal scalability, and reliability. 

Key features:

1. It combines the different type of searches

2. It makes use of APIs and JSON

3. It is workable with different programming languages like Python, NET, Java, and Groovy

4. It offers better security, monitoring, and reporting

5. It also offers machine learning features

6. You can do a real-time search using Elasticsearch-Hadoop

5. IBM SPSS Modeler- This is yet another great platform which has a wide range of algorithm and analysis tools to ensure faster and accurate analytics.

Key features:

1. Faster and better analysis of structured and unstructured data

2. Makes use of the intuitive interface 

3. You have the option of choosing between on-premises, hybrid and cloud deployment option

4. This tool can easily choose the best algorithm 

All these big data analytics tools are a must for every big data analytics learner. Any individual who wishes to become a big data analytics expert must undergo big data analytics training where they learn about these tools. Several other tools are there in the market, and a good big data certification program will introduce you to the same.