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In this video of Josh Money, Vidushi Chhabra is talking about how to get a job in Data Analytics. Data Analytics is one of the most trending jobs in India.
Data Analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Increasingly, data analytics is done with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions. Scientists and researchers also use analytics tools to verify or disprove scientific models, theories and hypotheses.
As a term, data analytics predominantly refers to an assortment of applications, from basic business intelligence (BI), reporting and online analytical processing (OLAP) to various forms of advanced analytics. In that sense, it's similar in nature to business analytics, another umbrella term for approaches to analyzing data. The difference is that the latter is oriented to business uses, while data analytics has a broader focus. The expansive view of the term isn't universal, though: In some cases, people use data analytics specifically to mean advanced analytics, treating BI as a separate category.
Data analytics initiatives can help businesses increase revenue, improve operational efficiency, optimize marketing campaigns and bolster customer service efforts. Analytics also enable organizations to respond quickly to emerging market trends and gain a competitive edge over business rivals. The ultimate goal of data analytics, however, is boosting business performance. Depending on the particular application, the analysed data can consist of either historical records or new information that has been processed for real-time analytics. In addition, it can come from a mix of internal systems and external data sources.
Data Analytics Tools
Now that we looked at the different steps involved in data analytics, let’s see the tools involved in data analytics, to perform the above steps. In this blog, we will discuss 7 data analytics tools, including a couple of programming languages that can help you perform analytics better.
1. Python: Python is an object-oriented open-source programming language. It supports a range of libraries for data manipulation, data visualization, and data modeling.
2. R: R is an open-source programming language majorly used for numerical and statistical analysis. It provides a range of libraries for data analysis and visualization.
3. Tableau: It is a simplified data visualization and analytics tool. This helps you create a variety of visualizations to present the data interactively, build reports, and dashboards to showcase insights and trends.
4. Power BI: Power BI is a business intelligence tool with easy drag-and-drop functionality. It supports multiple data sources with features that visually appeal to data. Power BI supports features that help you ask questions about your data and get immediate insights.
5. QlikView: QlikView offers interactive analytics with in-memory storage technology to analyze vast volumes of data and use data discoveries to support decision-making. It provides social data discovery and interactive guided analytics. It can manipulate colossal data sets instantly with accuracy.
6. Apache Spark: Apache Spark is an open-source data analytics engine that processes data in real time and carries out sophisticated analytics using SQL queries and machine learning algorithms.
7. SAS: SAS is a statistical analysis software that can help you perform analytics, visualize data, write SQL queries, perform statistical analysis, and build machine learning models to make future predictions.
Keywords:
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