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How Data Analytics Certification Can Boost Your Career?
The world is going digital, which means big data is going nowhere. In fact, the importance of big data and data analysis continues to grow in the coming years. Choosing a job in big data and analytics is a fantastic career move and may be exactly the role you want to find.
If you are thinking to have a career in this field, refer to the Data Analytics Online Training in Bahrain. This online training will shape you as an industry ready professional. Not just this, you can also customize the training as per your need. So if you want to prepare for the certification exam, then also you can enroll yourself in this Data Analytics training program.
Professionals working in this field can make a significant salary with an average salary of $116,000. Even people at the elementary level will earn a high salary with an average income of $92,000. As more companies recognize the need for big data analytics, these businesses continue to grow. About 80% of data scientists say that there is currently a shortage of specialists working in this field.
Reasons to Opt for a Data Analytics Certification
With big data analytics gaining widespread acceptance in the industry, let’s take a look at why tracking is so important to big data certification:
Get Highly Paid Job Roles
A data analytics certificate can increase your chances of achieving your desired position. With the right credentials, your resume can stand out from potential candidates, giving employers a reason to consider you superior.
After earning your data analytics certification, you will be eligible for a variety of roles, including:
- Data Analyst: The main responsibility is to collect information that influences business decisions.
- Data Visualizer: A data visualizer should create a dashboard on a weekly basis related to various aspects of a business’s sales such as customer behaviour, user flow, and so on.
- Business Intelligence Analyst: This role needs data analysis to identify market and business trends in order to assess the position of the company.
Enables You to Work in Any Field
Today, industries such as e-commerce, healthcare, finance, entertainment, and retail alike use big data to generate valuable information. To do this, they quickly hire data scientists. A data analytics certificate can enable you to work in any of these areas and discover future opportunities if they arise.
Requires Less Investment than University Studies
A data analytics professional certificate is relatively less expensive than a college degree and takes less time to complete. A certificate offers complete practical training that you can apply while on the job. This practical knowledge is always recommended and will better prepare you for works in any industry.
Shows Your Passion and Commitment
Certification reflects your potential employers your commitment and passion to your subject matter and study. It shows that you are serious about your career, with a sense of purpose in it. Employers know that most certifications offer unparalleled hands-on experience that can be applied to their business, and so they are always looking for such candidates.
Potential Salary Hike
As the demand for data analysts grows, organizations are ready to pay lucrative salaries to attract and retain the right talent. These salaries usually exceed the national average in the industry due to their vital role and importance. As you climb the corporate ladder and earn certifications, your salary increases at a rate unseen in any other profession or industry.
If all of the above mentioned reasons have intimated you to go for a certification, you must refer to the Data Analytics Online Certification in Kuwait. This online training will prepare you for the certification exam and will provide you with the industry-level knowledge.
Conclusion
If one is interested in working in data analytics, gaining a data analytics certification is a great way to build your skills and gain the knowledge needed to succeed in the rapid growth of data science.
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Your Data Architecture: Simple Best Practices for Your Data Strategy
If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
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Getting Started With Data Lakes
Frameworks for Efficient Enterprise Analytics
The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.
This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.
Introduction
As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).
This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.
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Top 10 Big Data Tools for Data Management and Analytics
Introduction to Big Data
What exactly is Big Data? Big Data is nothing but large and complex data sets, which can be both structured and unstructured. Its concept encompasses the infrastructures, technologies, and Big Data Tools created to manage this large amount of information.
To fulfill the need to achieve high-performance, Big Data Analytics tools play a vital role. Further, various Big Data tools and frameworks are responsible for retrieving meaningful information from a huge set of data.
List of Big Data Tools & Frameworks
The most important as well as popular Big Data Analytics Open Source Tools which are used in 2020 are as follows:
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- Data Preprocessing Tools
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