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Agriculture has moved on a long way from its traditional roots to the modern agriculture. As an industry, it has been evolved from a stage where it depended merely on submissions from soul farmers to a modern, data driven venture. Nowadays farmers are ready to tackle insights protected with a lot of historical data to return to a conclusive analysis on the crop to be planted and therefore the cultivation method to be used. Data Analytics is now suffocating old age agriculture processes to streamline irregularities and increase efficiency in cultivation, irrigation, harvesting, supply chain management, and logistics to make sure that there is a little to no risk involved when handling biodegradable goods. Brillica Services is the best Data Analytics Master’s Programming course in Dehradun, Uttarakhand and Delhi. The scope of massive Data Analytics in Agriculture lifecycle: IoT, Big Data, and Cloud computing are transforming the way agriculture functions as an Industry in India

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DAX refers to Data Analysis Expressions i.e. such expressions or formulas which are used for data analysis and calculations. These expressions are the collection and combination of functions, operators, and constants which are evaluated as one formula to extract the results (value or values). DAX formulas are very useful in Business Intelligence tools like Microsoft Power BI as they help the data analysts to use the data sets they have to the fullest potential. With the help of the DAX language, analysts can discover different new ways of calculating data values they have and come up with the new outcomes. Best Data Analytics Masters program course institute in Dehradun, Uttarakhand and Delhi. Know more about DAX concepts: • DAX is a functional language i.e., its absolute code is always a function. A feasible DAX expression contains conditional statements, nested functions, value references, etc. • DAX formulae have two primary data types; Numeric and Non-numeric or Others

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  When going to attend a DATA ANALYST job interview and wonder what are all the questions and discussions you will go through? Before you attend a Data Analyst’s interview, it's better to possess a thought of the sort of data analyst interview questions in order that you'll be mentally prepared and so have the answers to the questions. In this article, we will discuss about some most important Data Analyst interview questions and answers. Data Science and Data Analytics are both seems to be booming fields in the industry right now. Careers in these two domains are much escalating. The best part about looking for a career in the data science field is that it offers a wide range of career options to choose. Almost every organization around the world are strengthening the Big Data to enhance their overall productivity and efficiency, which unavoidably means that the demand for the expert data professionals such as Data Analysts, Data Engineers, And Data Scientists in ad

  We are, in all likelihood, living in the most defining period of human history. The period when computing moved from large mainframes to PCs and then to the cloud. But what makes it more defining is what is coming in our way in the upcoming years. What makes this period exciting and captivating for someone is the normalization of the various tools and techniques, which followed the boost in computing.   Widely, Machine Learning Algorithms are classified as: 1. Supervised Learning : Consists of a target / output variable (or dependent variable) which is to be predicted from a given set of predictors (independent variables). Using these set of variables, we generate a function which map inputs to desired outputs. The training process continues until the model achieves a desired level of accuracy on the training data. Some of the examples of Supervised Learning are Regression, Decision Tree, Random Forest, KNN, Logistic Regression etc.   2. Unsupervised Learning : In this,

In Excel , What-if analysis is a process of changing the value of the cells to see how the changes will affect the outcome. You can use different sets of values to explore all the various leads to one or more formulas. Nowadays, What-if Analysis in Excel is used by every data analyst and especially management professionals to make better, faster and more accurate decisions based on the data. What-if analysis tool is used in many situations, like: • To propose different budgets based on revenue. • To predict the future values based on the given historical values. • If you expect a certain value due to a formula, you can find different sets of input values that produce the desired result. To enable the what-if analysis tool you have to go to the Data menu tab and click on the What-If Analysis option. Goal Seek is a What-If Analysis tool which helps you to find the input value which results in a target value that you desire. Goal Seek requires a formula which uses the input

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 As it is known that there are different types of analytics to process the data, but many businesses don’t know when to hold what. In fact, what differentiate the best data scientist or data analyst from others is their capability to identify the right kind of analytics that best fits the best business needs to maximize the outcomes. Different types of analytics offer perceptible insights. In this article, we will learn about the five different types of analytics and their importance in our business.   Understanding the different types of analytics provided, added value to a business to improve its organization-level operational capabilities. Choosing the right form of data, analytics can make most of the unstructured or structured data they own.     Types of analytics to be discussed are: 1. Descriptive Analytics 90% of the organizations around the world uses descriptive analytics for working on the data. It is the simplest class of analytics that allows you to com

Linux is an open-source operating system just like Windows and MacOS . It is not only limited to the operating system , but it is also used as a platform to run desktops, servers, and embedded systems. It provides various distributions and variations as it is open source and has a modular design. The term called Kernel is the core part of the Linux system . Linux system is also used to manage various services such as process scheduling, application scheduling, basic peripheral devices, file system, and many more. Linux provides various advantages over other operating systems such as Windows and MacOS. Therefore, it is used in almost every field, from cars to home appliances and smartphones to servers (supercomputers).   Why Linux is far more better than other operating systems?   There are many features of the Linux operating system which illustrates that it is better than other operating systems. However, in some prospective, other operating systems can be more useful tha

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Data Science has emerged out as one of the popular fields of 21st Century. Companies hire Data Scientists and Data Analyst to help them gain insights about the market and to improve their products and services in better way. Data Scientists work as decision-makers and are responsible for analysing and for handling a large amount of organized or predefined data as well as raw data which have to be first organized to analyse. Data science is the field of study that consists of domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data scientists apply  machine learning with python  algorithms  to numbers, text, images, video, audio, and more to produce  artificial intelligence (AI) and deep learning to perform tasks that work on the human intelligence to make every field more precise. In turn, these systems generate  insights  which analysts and business users can translate into tangible business value. The

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  Power Query is used for data transformation and data preparation. Power Query consists of a graphical user interface for getting data from different sources and a Power Query Editor for filtering the data. Since the engine is available in many products and services, the destination where the data will be stored totally depends on where the Power Query was used. Using the Power Query editor, you can perform the extract, transform, and load (ETL) processing of data.   How Power Query helps with Data Acquisition: Business users consume up to 80 percent of their time on data preparation, which also delays the work of analysis and decision-making.     Transformations: The transformation engine in Power Query includes many predefined transformation functions that can be used through the graphical interface of the Power Query Editor. These transformations are often as simple as removing a column or filtering rows, or as common as using the primary row as a table header. T