Top Data Analytics Tools

If you have been in a data analyst job for some time now, you would know how much hard work goes into extracting and transforming the data into a usable format. But once this is done, data analytics can provide priceless insights into customers, business, and industry.

Here is a list of 10 best data analytics tools to extract meaningful insights from the data.

Tableau

Tableau is a data visualization tool for business intelligence. The software can connect to several local and cloud-based data sources and uses application integration technologies like JavaScript APIs for integration with common business applications. A highlight of Tableau is integrated statistical and geospatial functionality. 

Looker

Looker is a business intelligence software you can use to analyze and share real-time business analytics. It uses ELT approach to allow users to model and transform data according to their requirement.  The software features proprietary LookML language for constructing SQL queries against a database. Looker integrates seamlessly with Slack, Jira, and Segment.

Dataiku

Dataiku is a data science software platform useful in building data applications end-to-end.
It allows data scientists to source data, build predictive models, connect with data mining tools, and develop visualizations. Dataiku can be used to perform fraud detection, demand forecasting, lifetime value optimization, and spatial analytics.

Knime

Knime is an open-source, enterprise-class data analytics, reporting, and integration platform.  Using Knime, data scientists can perform a number of activities from extracting data to presenting insights without having to learn coding. The platform can integrate with other data science tools like H2O, R, Python, and Hadoop. Also, it supports medical claim outline detection, text mining, and social media sentiment analysis.

RapidMiner 

RapidMiner is a platform that allows technical and non-technical users perform a number of activities like data preparation, machine learning, and predictive analytics. The software delivers data science fast and easily. It can connect with several structured and unstructured data formats like Microsoft SQL, Sybase, MySQL, Ingres, Oracle, IBM DB2, IBM SPSS, dBASE, Excel, Access and text files.

Pentaho

Pentaho is a business intelligence software that provides data integration, data mining and extract, reporting, information dashboards, and load capabilities. It is particularly focused on data collection from IoT and integration with other data sources like ERP, CRM systems, Hadoop and NoSQL. This software features unique meta data injection and embedded analytics.

Talend

Talend is an open source software integration platform.  Its focus is to accelerate data integration projects. The software comes wizards to connect with Hadoop, Spark and the similar big data platforms. An important feature of Talend is that it makes data preparation easy and in turn facilitates access of clean and usable data easier.

Domo

Dome is a cloud-based business intelligence tool. It allows consolidation of data into one easy-to-use, self-service solution for several business roles facilitating timely access to data to decision makers. Using Domo, even less technical users can get data insights, quickly. A highlight of Domo is support to native mobile devices with the same experience as a desktop.

Sisense

Sisense is an end-to-end analytics platform that reveals business insights from complex data that has come from any data source or is of any size. The software can be deployed on premises, Sisense-managed environment and private cloud.  It facilitates strong governance at user, object and data levels. Sisense allows integration of components like JavaScript APIs, single sign-on and customization of embedded visualizations.

Qlik

Qlik is a data management and analytics platform. A highlight of this platform is the associative engine that automatically profiles data from sources, identifies linkages, and provides a combined data set. Qlik’s in-memory processing architecture allows several users to concurrently explore large and diverse data sets.