Data Analytics Skills & Applications

Data Analytics Overview

Introduction to Data Analytics

Data Analytics is all about Extracting information out of the Data, Data Profiling, Data Cleansing and Data Deduping

Data Analytics is the science and the Process of analyzing data sets. This is to extract information and draw Conclusions from the Data. This kind of analysis helps the Organization in making better and more informed Business decisions.

Data Analytics is the Process of gathering, storing, processing Data and creating solid approach of Problem Solving Methods. There are various Data Analytics Tools available to help and make the Data Analytics Task easier.

Advantages of Data Analytics

  • Error Detection
  • Removes Duplicates
  • Machine learning algorithms for advertisements
  • Risk Reduction
  • Transmits Useful Information
  • Establishes a Uniform Platform
  • Holistic approach

Data Analytics Advantage

Following are the advantages of Data Analytics:

  • Error Detection:

Before Data Cleansing, it detects and corrects the Errors present in the Data Set.

  • Removes Duplicates:

Saves a large amount of Memory space in the system as Data Analytics helps in removing all the Duplicates present in the System. This results in Cost Reduction of the Company.

  • Machine learning algorithms for advertisements:

There are Machine learning algorithms that are being used for displaying relevant advertisements on the online shopping websites. This is Based on the ancient and Historic Data. It helps to increase the Revenue of the Company.

  • Risk Reduction:

Data Analytics Process thoroughly studies the Customer Profile and History and then provides them the Loan or services to the applicants. This helps in preventing the banks from any wrongdoings and/or calamities

  • Transmits Useful Information:

It aggregates and normalizes the data to transmit useful information. It helps in clinical integration, preventive care and Disease Management

  • Establishes a Uniform Platform:

Manages huge Volume of Data be it advanced, clinical, or about the safety of the Patient. Allocating and Reporting the Resources equally to the people via Government.

  • Holistic approach:

Providers understand and interpret information coming through the nontraditional sources—This could be a socio-economic factor, a specific physical health-related factor or administering care at a holistic level. Providers will obtain the Information needed from the IT infrastructure which will collect and analyze the information from different sources, facilitates data search, and provides the appropriate analytics which aids for better decision making.

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Application of Data Analytics

  • Higher Security Level
  • Transportation Management
  • Fraud Detection
  • Manages Risk
  • Delivery Logistics
  • Minimizing inefficiencies through predictive analytics
  • Optimizing Marketing Strategies

Data Analytics Application

There are skills that are must to get a Data Analyst Job. Let’s look at these skills in detail:

  • Higher Security Level

With the availability of Data, the Security game has been on the hike. The Officers are alert during the Particular predicted hours when there was a rise in the Crime Rate. Data Analytics has made it possible to have Safer Cities and has led to a drop-in crime rate.

  • Transportation Management

Data Analytics lends you the Data of the events that were previously held. This allows you and grants you the Opportunity to do the Crowd Management. You have a clear demonstration in front of you and now you just need to Organize the Transportation accordingly and Manage the People.

  • Fraud Detection

Data Analytics makes it easier for the Banks and Financial Firms to study the Customer Profile and significant information that was made available before Granting loans to the Customers. This made it easy for them to analyze and infer if at all there was the chance of customers defaulting.

  • Manages Risk

Data analytics helps the insurance companies gain knowledge about the claimed data, actuarial data as well as the risk data. This helps the Company in taking important Decisions. Automation is improving claims processing efficiency, with Data Analytics various forms of fraudulent claims are detected. It helps the administrators to Manage the Risk.

  • Delivery Logistics

UPS, DHL, FedEx, etc. are Companies that working on data for improving their efficiency in operations. Data analytics applications which helps them to find the most suitable routes for shipping, the most suitable means of transport and the best delivery time which makes the Companies Cost Effective. Using GPS gives them the opportunity to take advantage of data analytics and data science.

  • Minimizing inefficiencies through predictive analytics

Organizations are taking advantage of Big Data analytics. Combining the Business Intelligence tactics and Predictive Analytics. This helps to gain the edge over their competition.

Here are a few applications of predictive analytics in industries:

  • Optimizing Marketing Strategies:

Predictive analytics helps in forming effective strategies for identifying, pulling and capturing markets by creating the products and service base.

Now Capture usage patterns and past search data of website visitors and recommend products to the Customers.

Skills Required for Data Analyst

  • Analytical Skills:
  • Numeracy Skills
  • Technical and Computer Skills
  • Attention to Details
  • Business Skills
  • Communication Skills

There are skills that are must to get a Data Analyst Job. Let’s look at these skills in detail:

  • Analytical Skills:

The ability to gather, observe and analyze all kind of information,

  • Numeracy Skills

Good Mathematical Skills. Knowledge of Figures and Numbers. It is to understand the relationship between numbers and the interpretation of the Mathematical information and Methods.

  • Technical and Computer Skills

Statistics, Computer Skills and Technical Skills are must to become a Data Analyst. Data Analysts should be familiar with the basic Softwares like: scripting language (Matlab, Python), Spreadsheet, programming (JavaScript, XML) and few other Data Tools

  • Attention to Details

Developing the Ability to recognize and remember unseen Patterns and Links. Once you pay Attention to Details, your chances of Making errors goes down.

  • Business Skills

You need to have a clear Decision-making and problem-solving skill, ability to acquire knowledge on new things, ability to communicate effectively with directors and co-workers and effective Time Management Techniques.

  • Communication Skills

Excellent Communication Skills to be able to handle Meetings, make effective decisions and rock the Social Media Platforms

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Conclusion:

  • If you take a quick look around the Market sectors, you’ll see everyone has become an e-commerce player of Data Analytics.
  • Data Analytics is now a part of almost every operation. It is being used for Recourse Management and Forecasting the Inventory
  • Every Business or industry uses Data Analytics to determine future occupancy rates to adjust accommodation prices, to determine what discounts can be given, to determine the date and Time of Promotion and to figure out the exact ROI
  • The best Part is, the decision is no more dependent on the gut feeling but the system is completely data-dependent.
  • The Combination of Data science and Analytics has Surpassed almost every sector. This has helped almost all the Organizations in better and enhanced decision Making.