Is There Any Scope of Doing Dell EMC Advanced Analytics Specialist Certification?

Dell EMC Advanced Analytics Specialist Certification Overview

The Dell EMC Advanced Analytics Specialist is a certification that exposes to the big data and data analytics. Topics for this certification cover an introduction to data analytics, characteristics of big data, and data scientists' role. It also held a variety of big data theories and techniques, including linear regression, time-series analysis, and decision trees.

Various tracks are within the Proven Professional program, allowing certificate holders to achieve a depth of knowledge in particular areas of Dell EMC products and storage technologies. Proven Professional courses include data scientist, cloud architect, cloud and storage administrator, technology architect, engineer, and application developer. Dell EMC advances product-specific certifications for customers who employ ScaleIO, ViPR, Data Protection Advisor, and VxRail storage solutions.

Most, but not all, Proven Professional tracks come in three levels: Associate, Specialist, and Expert. Each certification track in the Proven Professional program points to combine target audiences – employees, partners, customers, and industry-wide.

The next level up on the certification ladder is the Dell EMC Data Scientist, Advanced Analytics Specialist. Professionals at this level use advanced analytics to solve business issues. They use Hadoop, Pig, Hive, and HBase; analyze social networks, and understand natural language processing.

Benefits of Dell EMC Advanced Analytics Specialist Certification

Data exploration and data discovery to recognize and quantify the characteristic of the data. This is an interactive method to learn which variables and metrics to test in the interactive analytic model development process.

Data improvement is the method of creating new higher-order variables that improve the raw data's content and meaning, given the difficulty being addressed. Data advancement methods cover log changes, recency, frequency, monetary, calculations, indices, share, attributions, and scores.

Data visualization uses tools and methods to recognize patterns, trends, outliers, and correlations that might be important in the analytic modeling process; to know variables and metrics that might be better predictors of business and operational performance.

Feature engineering, creating new input features for machine learning, is one of the most effective methods to develop predictive models.

The Career Prospects After Passing Dell EMC Advanced Analytics Specialist Exam

Today, almost all companies use IT deployment services. They need IT professionals, data scientists, specialists, implementation engineers, and technology architects. The HR manager or enterprises give preference for certified implementation engineers, scientists, and specialists.

After passing this Dell EMC Advanced Analytics Specialist (E20-065) exam, you will be in a better position to get a job. You can increase your credibility and confidence. To distinguish yourself in the market, you have to get this credential with good marks. You can start and advance your career in the following job roles.

Data Scientist Requirements

Each industry has its big data profile for a data scientist to investigate. Here are some of the more popular forms of big data in each sector, and the sets of analysis a data scientist will likely be required to perform.

• Business: Today, data shape the business strategy for nearly every company, but companies want data scientists to make sense of the information. Data analysis of business data can tell decisions around performance, inventory, production errors, customer loyalty, and more.

• E-commerce: Now that websites get more than purchase data, data scientists help e-commerce businesses increase customer service, find trends, and promote services or products.

• Finance: In the finance industry, data on accounts, credit and debit transactions, and related financial data are essential to a functioning business. But for data scientists in this field, security, and agreement, including fraud detection, are also significant concerns.

• Government: Big data aids governments form decisions, support constituents, and monitor overall satisfaction. Like the finance sector, security and agreement are paramount concerns for data scientists.

• Science: Scientists have always managed data, but now with technology, they can better collect, share, and analyze data from experiments. Data scientists can help with this process.

• Social Networking: Social networking data help inform targeted advertising, improve customer satisfaction, establish trends in location data, and improve features and services. Ongoing data analysis of posts, tweets, blogs, and other social media can aid businesses in improving their services continuously.

• Healthcare: Electronic medical records are now the standard for healthcare facilities, which need dedication to big data, security, and compliance. Here, data scientists can aid promote health services and uncover trends that might go unseen otherwise.

• Telecommunications: All sciences collect data, and all that data requires to be stored, managed, maintained, and analyzed. Data scientists help the company's squash bugs, improve products, and keep customers happy by delivering the features they want.

• Other: No industry is immune to the big data push, and you will find jobs in different niche areas, like politics, utilities, smart appliances, and more.

Keys Takeaway

From my perspective, the Dell EMC Advanced Analytics Specialist is useful for someone who has knowledge about data science or has trained a couple of predictive analytics models.

Through the study, we learn the process of training the model, building a pipeline for the experiment, and deploying the model to production in an efficient way. In my opinion, it is not only suitable for the Dell EMC Advanced Analytics Specialist but also helps you have the idea of real-world processes even on other platforms.

It is no secret that data scientists can bring an immense amount of value to the table. Finding one person who can do all the tasks expected of a data scientist is challenging, and controversy over hiring these professionals is hard.