Big Data plays a vital role in our everyday lives and impacts virtually everything we do. Analyzing this huge data has become a big business opportunity in recent years that has led to the need for Big data analysts. As it is a new and growing field so there is a lot to learn frequently. Big data is a collection of data that is huge in volume and growing exponentially with time. It is so large in size and complex that none of the traditional data management tools can process it or store it efficiently.
There is a big data hadoop course for beginners available to help, explore, and understand the Big Data concept essential for a successful career. Big data is categorized into three types as Structured, Unstructured, and Semi-Structured. Where structured data can be accessed, stored, and processed in the form of a fixed format, any data with an unknown form or structure is known as unstructured data. It poses multiple challenges in terms of its processing for deriving value out of it. Semi-structured data can contain both forms of data that are structured in the form but it is actually not defined.
Big Data can be described with the characteristics such as Volume, Variety, Velocity, and Variability. Where volume is related to the huge size of data, variety refers to heterogeneous sources and the nature of data, velocity refers to the speed of generation of data, and variability refers to the inconsistency that can be shown by the data at a time.
This article lets you understand who is a Big Data Analyst and what skills and steps are required to become one.
Who is a Big Data Analyst?
A Big Data analyst is a person who focuses on uncovering and analyzing useful data like patterns and hidden trends so companies can make more informed business decisions and gain a competitive advantage. Big data analysts study the market by identifying, collecting, communicating, and visualizing this data to help guide these future decisions. They can wear multiple hats and also they can frequently switch gears from conducting research to mining data for information to presenting findings. Big data analytics are problem-solver professionals who have the ability to think critically and logically while using creative reasoning skills. A successful big analyst should also have programming knowledge, quantitative data interpretation skills to perform their task successfully.
Simply, a big data analyst delivers value to their companies by taking information about particular topics and then interprets, analyzes, and presents findings in their comprehensive reports. They are often called on to use their skills and tools to provide meaningful analysis and find trends within industries.
Roles and Responsibilities of Big Data Analysts
The roles and responsibilities of Big Data Analysts basically depend on their level of expertise. So they may have the following roles:
- Determine Organizational Goals- The first and most crucial role of a data analyst is to determine an organization’s goal. To set the goal and do planning, they work with IT Teams, Management, and Data Scientists.
- Mining Data- It is the beginning process to structure the raw data and recognize or formulate the various patterns in the data with the help of computational and mathematical algorithms. So data analysts have to collect and mine data. They get their data from the company databases or extract it from outer sources to do any sort of research.
- Data cleaning- Data cleansing is the process of identifying, analyzing, and correcting messy, raw data as it is the first step in the overall data preparation process. This process involves removing data that may distort analysis or standardizing your data into a single format. It is also used for analyzing organizational data to make strategic decisions.
- Analyzing Data- To analyze data is a must for any data analyst that explores the facts from the data with specific to answer a specific question. It evaluates data using analytical and logical reasoning to examine each component of the data received. Data analysts use statistical tools to analyze and interpret the data. There are many programming languages and tools used in analysis processes.
- Pinpointing Patterns and Trends- Data analysts find trends and patterns and correlations in complex datasets. They look for short-term and long-term trends as both are important.
- Create reports with Clear Visualization- It is a crucial job to translate raw data into information that is called reporting. It helps companies to monitor their online businesses and be alerted to when data falls outside of expected ranges. Data analysts use high-quality, eye-catching graphs and charts to present their findings in a clear and concise way to effectively visualize their reports.
Big Data analysts also maintain databases and data systems to ensure that the availability, storage, and coherence of electronically stored data meet an organization’s needs. So their role is very important for any organization to achieve business goals.
Skills Required To Become A Big Data Analyst
To become an expert Big Data Analyst there are some of the technical key big data skills to achieve, mentioned below.
- Programming- A Big data Analyst must be very comfortable with coding and programming languages. Big Data is an evolutionary field so programming skills are required for data analysts as a lot of customization is required on a daily basis to deal with unstructured data. Programming languages like Python, R, C++, Java, Hive, SQL, Ruby, MATLAB, Weka, Scala, Julia, SAS, SPSS fall under Data Analyst requirements.
- Data warehousing- To become an expert bid data analyst, it is necessary to have data warehousing skills and experience with relational and non-relational database systems. The relational database involves Mysql, DB2, and Oracle while HDFS, Hbase, Couch DB, MongoDB, Cassandra, Teradata are some examples of the non-relational databases.
- Computational Frameworks- A good familiarity and understanding of frameworks is also a must-have skill for data analysts. It involves Apache Spark, Apache Storm, Apache Flink, and the classics MapReduce and Hadoop that help in Big Data Processing which can be streamed to a great extent.
- Quantitative Aptitude and Statistic- As the processing of big data requires great use of technology, so the basic to any analysis of data is good knowledge of statistics and linear algebra. Statistics is a foundational building block of data science so knowledge of core concepts like probability distribution, summary statistics, hypothesis testing, and random variables are crucial data analyst skills to possess.
Business knowledge, Data Visualization are also must-have skills required to become a big data analyst. So it is important to know what big data skills you require to start working with data. Gain and improve your data skills to gain more opportunities and attractive salary packages in the future.