It’s the method of collecting both quantitative and qualitative information about a digital property. For example, Data analytics tools look like Mixpanel or Google Analytics which both allow you to track metrics like how many visitors came to our website.
What is Data cleansing?
It helps Data analyst have to discover and eliminating errors from the database to improve data quality.
Difference between data mining and data profiling?
Data mining is aiming to unusual record detection, sequence discovery, Cluster analysis and others. Data profiling targets individual attributes analysis like value ranges and their data types, length, frequency.
Define challenges faced by a Data Analyst?
Here I mention a few challenges, Value misrepresentation Duplicate entries Identify Data overlapping Illegal values
Define Outlier?
When data analyst tries to refer a value that appearing very far away from the pattern in a sample. Here we are having two types, 1.Univariate, 2.Multivariate.
How could you find a solution to Multisource problems?
Identify the similar records and put them together into a single record that contains a needed attributes. To achieve schema integration we have to restructure the schemas.
Describe K-Mean Algorithm?
The K Means Algorithm is a way to find a cluster in your data, It has set of steps to find a group and label the data. It's like a partitioning method where objects are classified into K groups.
Define collaborative filtering?
It is a process of filtering using techniques among multiple users. Collaborative filtering has two senses one is narrow one another is more general one. It actually does automatic predictions filtering.
What is Map Reduce?
Mapreduce is a Programming model, Map method performs filter and Sorting and Reduce method perform a Summary operation. It can able to run various tasks in parallel.
Describe Series Analysis?
Series Analysis can be done in 2 domains, Time Domain and Frequency Domain. Time Series Analysis when the output process is forecasted by analysing data gotten previously using methods including exponential smoothing, log-linear regression.
Skills set for a Data Analyst:
As a Data Analyst must start by ensuring good Mathematical knowledge, technology and also a business intelligence and statistics. He should be good at below mentioned skills, Analytical Skills - Handle the Situation from different perspective Mathematical Skills – Calculation and graphical information Computer Skills – Scripting language, Querying language, Programming Business Skills – Decision making and time management and organization skills.
PreRequisite to learn Data Analyst:
Programming Language – Preferably Python Algorithms – Understanding the concepts and Data Structures Database – Basic knowledge of MySQL Mathematics – Probability, Algebra, Statistics
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