Understanding Data Analytics

Understanding Data Analytics

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Data analytics is the process of analyzing poised data in order to help companies make knowledgable business decisions. For that, organizations analyze the data in order to help divulge hidden values. Just as critical, they also make endorsement for how to amend business performance. Data analytic organizations can analyze inventory data advice manufacturers exceptional plan when to purchase parts, authorize how long those parts should be stored, and identify where absolutely to house the inventory – thus improving business operations and performance.

As more organizations implement big data strategies, data analytic companies advice these organizations identify performance issues and make informed business decisions to enhance and optimize results. Those that decline to weight the information in their data, or do it ailing, will suffer cutthroat burden and objections. It is imperative for organizations to invest in and invigorate their data analytic competence.

Data Analytic Process

Data analytics companies employ some form of the following for conducting data analyses strategies and activities:

1. Business requirements need to be carefully inferred with a plan designed for apprehending and safely securing the suited data

2. Business data needs to be collected, cleansed, and organized in a demeanor so that the data can be analyzed

3. Business data is analyzed, outcomes rendered, and intuition provided which may or may not cover visualizations

Data analytics companies have implemented competence to back specific types of business locale, counting information management, machine learning models, and the processing of personal data as origin of information. Data analytics companies often develop analytics effectiveness that are designed to acquire user action. They can also apply capabilities to help automate business processes, provide product support, and provide customer service.

Three different models of Data Analytics

In order for data analytic companies to convey key insights, data professionals utilize any of three types of analytics. These are descriptive analytics, predictive analytics, and prescriptive analytics.

Descriptive analytics: Descriptive analytics assesses historical data to better understand changes that have occurred in a business. The purpose of descriptive analytics is to answer the question “what has happened?”. This is the simplest form of analytics and many companies employ descriptive analytics in their organization.

Predictive analytics: Predictive analytics makes predictions about future outcomes based on historical data combined with analytical techniques. It is an integrated, interactive analytics program aimed at improving the performance and efficiency of its operations in the future. The purpose of predictive analytics is to answer the question “what may happen?” Predictive analytics is a forecasting technique.

Prescriptive analytics: Prescriptive analytics focuses on identifying the best course of action in a scenario given the available data. It also suggests courses of actions that depend on the results of descriptive and predictive analytics. Optimization scenarios are assessed to answer “what should we do?”.

Platforms and Tools

Some of the more famous tools utilized by data professionals and data analytics companies include the following:

Apache Spark: Apache Spark is an open source big data platform which combines data science with web analytics to provide a high-quality, data driven, and accurate analytics solution to applications.

Python: Python is an open source scripting language which is easy to learn and has a plethora of libraries, many of which are useful to data professional.

R Programming: R is an open source programming tool primarily used for statistics and data modeling provided by the R Foundation for Statistical Computing.

Power BI / Tableau: Power BI & Tableau are interactive data visualization software tool used by data analysts, data scientists, and others to present data in a meaningful and interactive way. Both tools have a free version as well as paid version of their visualization tool.

SAS: SAS is an analytics platform offered by the SAS Institute which helps organizations access, manage, analyze and report on data to aid in decision-making.