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Top 8 Big Data Analysis Tools That Every Data Analyst Must Know

Currently there are many paid and open source data Analysis tools that are being used by organizations of all sizes.  In the present time, organizations are increasingly utilizing data analysis tools to crunch large set of data and convert it into meaningful visualizations including graphs, charts, or interactive dashboards. Gone is the time when such complex information was contemplated over spreadsheets making it a tedious procedure. With data analysis tools and visual examination, one can without much stress can handle a lot of data now.  There are a vast number of tools available for data analysis in the market for today. In this blog post, we will list 8 top data analysis tools including the popular open source data tools, data extraction tools, sentiment tools, data visualization tools, and databases.

R

R is currently one of the most popular analytics tools for data scientists. It has outperformed SAS in its use and has now became a priority tool even for big organizations that can very easily deploy paid enterprise tools like SAS. In recent years R has turned into a significantly strong platform. It can handle vast data sets and is also amazingly flexible.

The R language is broadly utilized tool among data miners for creating the data analysis and statistical program. Other than data mining it offers graphical and statistical procedures, including nonlinear and linear modeling, standard statistical tests, time-series analysis, clustering, classification, and so on.

Spark

Apache Spark is one of the most incredible open source big data tools. Apache Spark was designed to fill the shortcomings of Hadoop especially related to data processing. Spark is many times faster than Hadoop in data processing. Spark’s fast data processing speed is due it’s in memory processing as compared to Hadoop’s traditional in disk processing.  It also has built-in APIs for Python, Java, or Scala.

 Zoho Analytics

Zoho Analytics offers diverse reporting features, including KPI widgets, tabular view components, and pivot tables, enabling it to produce reports that offer great insights. The Zoho analytics platform allows collaborative analysis and review, allowing the clients to work with co-workers on report improvement and central leadership.  The platform offer extremely easy to use –  drag and drop visual interface – which means users don’t need coding experience with Zoho analytics.

Tableau

Tableau Is a data analysis and visualization tool which can connect with many data sources comfortably. The big advantage with Tableau is its ability to create interactive dashboards. These dashboards can be created without much coding knowledge, through visual intuitive drag and drop interface.  Tableau has been very popular among organizations due to its ability to translate data into insightful visual dashboard. Lastly, Tableau utilizes application integration innovations like JavaScript APIs and single sign-on application to include Tableau analytics into basic business applications consistently.

Hadoop

Hadoop is simply the most widely used data analytics tool currently in the industry. Hadoop is completely open source data processing tool which offers processing and storage of big data. Hadoop is extremely flexible in processing big data – as it can handle structured as well unstructured data.

Mongo DB

Mongo DB is a flexible NoSQL based database system.  This is one of the good resource for data which isn’t structured.  The top features of Mongo DB are :

  • Load balancing – Mongo DB offers a database platform which can run smoothly even when load is high as it can run over multiple servers while balancing the load among them.
  • Ad hoc query – Mongo DB supports ad hoc queries such as field or range query.
  • File storage system – Mongo DB is also being widely used as an efficient file storage system which can store files across multiple servers while using load balancing feature.

Chart.io

It’s a drag and drop chart production cloud based tool that can function well on a computer or tablet. Chart.io can connect with various types of data sources and databases, ranging from MySQL to Oracle. Data can be sourced and integrated from various sources with a single tap of a button before performing the analysis. It can create an assortment of charts, graphs for example, pie charts, bar graphs, scatter plots etc. Chart.io is extremely popular among marketers for performing marketing analytics.

KNIME

KNIME enables you to control, analyze, and to demonstrate data in an unimaginably intuitive mode with the help of visual programming. KNIME can be used to run python, R, chemistry data, text mining, and others, which gives you the alternative to dabble with the further developed code driven analysis. The tool is finding its use in customer data analytics, pharma research, financial data analytics.  KNIME is fast becoming an open source alternative to SAS.

The post Top 8 Big Data Analysis Tools That Every Data Analyst Must Know appeared first on AcadGild.



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Top 8 Big Data Analysis Tools That Every Data Analyst Must Know

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