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Time Series Analysis Part I

 

A time series is a sequence of numerical data in which each item is associated with a particular instant in time. Many sets of data appear as time series: a monthly sequence of the quantity of goods shipped from a factory, a weekly series of the number of road accidents, daily rainfall amounts, hourly observations made on the yield of a chemical process, and so on. Examples of time series abound in such fields as economics, business, engineering, the natural sciences (especially geophysics and meteorology), and the social sciences.

  • Univariate time series analysis- When we have a single sequence of data observed over time then it is called univariate time series analysis.
  • Multivariate time series analysis – When we have several sets of data for the same sequence of time periods to observe then it is called multivariate time series analysis.

The data used in time series analysis is a random variable (Yt) where t is denoted as time and such a collection of random variables ordered in time is called random or stochastic process.

Stationary: A time series is said to be stationary when all the moments of its probability distribution i.e. mean, variance , covariance etc. are invariant over time. It becomes quite easy forecast data in this kind of situation as the hidden patterns are recognizable which make predictions easy.

Non-stationary: A non-stationary time series will have a time varying mean or time varying variance or both, which makes it impossible to generalize the time series over other time periods.

Non stationary processes can further be explained with the help of a term called Random walk models. This term or theory usually is used in stock market which assumes that stock prices are independent of each other over time. Now there are two types of random walks:
Random walk with drift : When the observation that is to be predicted at a time ‘t’ is equal to last period’s value plus a constant or a drift (α) and the residual term (ε). It can be written as
Yt= α + Yt-1 + εt
The equation shows that Yt drifts upwards or downwards depending upon α being positive or negative and the mean and the variance also increases over time.
Random walk without drift: The random walk without a drift model observes that the values to be predicted at time ‘t’ is equal to last past period’s value plus a random shock.
Yt= Yt-1 + εt
Consider that the effect in one unit shock then the process started at some time 0 with a value of Y0
When t=1
Y1= Y0 + ε1
When t=2
Y2= Y1+ ε2= Y0 + ε1+ ε2
In general,
Yt= Y0+∑ εt
In this case as t increases the variance increases indefinitely whereas the mean value of Y is equal to its initial or starting value. Therefore the random walk model without drift is a non-stationary process.

So, with that we come to the end of the discussion on the Time Series. Hopefully it helped you understand time Series, for more information you can also watch the video tutorial attached down this blog. DexLab Analytics offers machine learning courses in delhi. To keep on learning more, follow DexLab Analytics blog.


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Not to Miss: The Startup India tableau at Republic Day 2020 parade

Not to Miss: The Startup India tableau at Republic Day 2020 parade

The commerce and industry ministry recently, in a written press briefing, said that it will showcase a tableau on Startup India, with an aim to promote innovation and entrepreneurship in the nation. The tableau will be displayed at the Republic Day Parade this year, in a first.

The name of the tableau is ‘Startups: Reach for the Sky’. It is themed on the stages of the life-cycle of a startup and the multifarious elements of support provided by the government, the ministry said in a press statement.

“The front of the tableau depicts a creative mind, full of ideas to solve real world problems. The Startup India Tree, in the middle will represent different kinds of support given,” a government official from the Department of Promotion of Industry & Internal Trade (DPIIT), said in the statement.

The staircase will stand for the various stages of growth – those are – coming up with a concept, creating a prototype, preparing a business plan, building a team, launching into markets and eventually scaling up, an Economic Times report said.

The wheel will denote sectors of economy where Indians have driven and given a fillip to economic growth and created employment opportunities on a big scale, the statement read. The wheel and the map of India together depict the width and the depth of the Startup India movement in the country.

Startup India is a flagship initiative of the Narendra Modi government, conceived with the intention of building a strong environment to nurture innovation, drive sustainable economic growth and generate large scale employment opportunities and job openings.

“We have a million problems, but at the same time we have over a billion minds,” Prime Minister Narendra Modi had said about the flagship programme started in January, 2016. In October, 2019 Prime Minister Narendra Modi said that the Indian startup ecosystem will help India achieve the $5 trillion target for the economy set by the government.

The objective is to inspire and motivate youth to follow their dreams to generate wealth and become job creators and not just job seekers. Under the Startup India Scheme, eligible companies can get recognised as startups by the ministry in order to access a host of tax benefits, easier compliance, IPR fast tracking and other incentives.

More than 26,000 startups from 551 districts of 28 States and 7 Union Territories have been recognized so far. “Working across IT, Industry 4.0, education, healthcare, agriculture, energy, finance, space, defence and all other sectors of economy, Indian startups have attracted substantial global investments and created more than 2,91,000 jobs,” it added.

Besides DPIIT, the Department of Financial Services, Department of Drinking Water and Sanitation, NDRF Ministry of Home Affairs, CPWD Ministry of Housing and Urban Affairs, and Ministry of Shipping will also participate in the Republic Day parade.

 

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Why Tableau Is the Best Data Visualization Tool for Industries Worldwide?

Why Tableau Is the Best Data Visualization Tool for Industries Worldwide?

There are several data visualization tools available in the market but Tableau is the most popular and effective. Most of the key players from the BI industry depend on this software for transforming raw data into an easy-to-understand format.

What Makes Tableau So Popular?

Tableau is frequently used as a tool that helps to analyze data quickly and creates visualizations for worksheets and dashboards. It lets users design dashboards that generate actionable insights and takes businesses to new heights. Below, we’ve rounded up top 4 reasons why businesses rely on Tableau:

Amazing Visualizations

Tableau allows you to work with more unordered data and develop stunning visualization: courtesy an array of in-built features. You can also achieve superb context, different ways of drilling meaningful data and understand data in minutes.

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Detailed Insights

The best thing about this visualization tool is that it lets you analyze future data; you can do that while observing data from several angles and approaches. Plus, you can frame hypothetical queries and work on that data correspondingly – possible only because of the feature of adding elements for comparison and analysis and ‘what-if’ visualizations!

Simple Approach

Being user-friendly is one of the major strengths of Tableau. Thanks to this feature, users with no coding or technical knowledge can use Tableau easily. Since most of the features are in a drag-and-drop format, any newbie can work on Tableau without possessing a prior set of skills.

DexLab Analytics is one of the most popular Tableau training institutes in Delhi. Take a look at their offerings.

Works With Various Data Sources

This is what makes Tableau an absolute essential for business houses! In Tableau, data can be taken from anywhere irrespective of its sources. This feature makes it powerful as compared to other BI and Analytics tools. It lets you connect diverse data sources, cloud files, spreadsheet data, big data, data warehouses and various other types of data, including non-relational ones. The software can blend any kind of data to create amazing visualizations that are bound to garner admiration.

Are You Ready?

As of endnotes, a large number of Fortune Global 500 companies prefer Tableau over other data visualization tools. And why not! It is user-friendly and can solve complex business problems and prepare phenomenal visualizations within minutes.

If you are interested in pursuing a business intelligence career, check out Tableau Certification Delhi. Such certification course will push your career to new heights. It will be a good start for your analytics career and you will get better opportunities to succeed.

Enroll now: <www.dexlabanalytics.com/courses/tableau-bi-visualization-certification>
 
The blog has been sourced from: www.knowledgehut.com/blog/business-intelligence-and-visualization/why-tableau-is-so-popular
 

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Importance of MIS in Business

Importance of MIS in Business

Today’s corporate world is dynamic. Ever-evolving technologies and daily upgrades drive business organizations to fulfill goals and objectives. They also involve substantial risks and uncertainties. These challenges urge businesses to take crucial decisions that end up determining their future success. Since the primary objective of any organization is to improve their profit ratio and flourish in the long run.

This is why businesses can’t ignore the significance of MIS – Management Information System

Define MIS

MIS is a comprehensive set of processes that offers critical data and information to the management so as to enhance informed decision-making. It involves:

  • Gathering apt data from numerous reliable sources
  • Processing of those data to derive meaningful, relevant information
  • Furnishing this essential information to the respective department

What Makes MIS Reports so Important to Boost Business Decision-making?

MIS Reports are prepared after careful analysis of existing data and observing on-going trends prevalent in the industry. They play a key role in improving productivity, performance and profitability of any enterprise. No wonder, it’s extremely important for the administration to lay hands on reliable data in sync with the latest trends to make quick, informed decisions.

As a result, MIS Reporting System is regarded as the bedrock of company operations, and it aids the company to stand out against its tailing rivals.

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Advantages of MIS

Efficient Data Management

MIS is widely favored for managing essential business data to aid in complex decision-making. The high on significance kind of information is stored in an efficient way and can be easily accessed by the administration anytime anywhere.

Trend Analysis

Management in any organization needs to prepare a presentation for strategic planning and tabulate future goals. In order to create such advanced strategies, they need to possess accurate reports clearing in accordance with prevailing market situations. MIS uses numerous mathematical tools that would analyze current market trends and precisely predict future trends based on such details.

MIS Sets Future Goals

Be it a finance firm, an MNC, a healthcare institute – setting up a goal matters a lot. It requires ample research and development. The information derived from MIS Reports is held veritable and is mostly used to determine company goal. Also, MIS requires current market trend analysis and future industry forecasts. Thus, it won’t be prudent enough to ignore MIS and reporting.

Improved Efficiency

The appropriate information collected by MIS helps in formulating improved goals and top notch strategies for the company. Also, the performance can be easily gauged with the help MIS Reports. Undeniably, MS plays a crucial role in enhancing the efficiency of the organization.

Compare and Contrast

MIS database is encompassing and can be accessed anytime. Management professionals can anytime go through the MIS reports and compare and contrast its present business performance with that of previous years’. Often this helps in measuring company’s growth prospects and if it’s on the right track towards success.

In a concluding note, we would recommend Best MIS Training in Gurgaon; DexLab Analytics is a sure bet when it comes to the best MIS training institute in Delhi. With skilled experts in the team, the institute is one stop shop for all things data analytics.

 
The blog has been sourced from ― aristotleconsultancy.com/blog/mis-important-businesses
 

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Top 3 Data Visualization Tools Trending Now

Top 3 Data Visualization Tools Trending Now

The wave of digital transformation is ravaging all industry verticals. Big Data coupled with AI and ML is driving the force, with data being at the bull’s eye.

But, what if we say most of the data in the world is hardly used? What if it becomes a hefty liability? Yes, data can become a liability if we fail to understand it properly. For that, we’ve data visualization – it’s the best way to present your data to the world in order to gain meaningful insights.

Fortunately, data visualization is evolving rapidly. Charts, graphs, infographics, videos and AR/VR presentations have taken the channels of communication to an entirely different level. In this blog, we’ve compiled tip 3 most popular and effective data visualization tools – they are easy to use, do their job well and highly compatible with major software and programming languages. However, they are all paid, although they offer free-trials.

Tableau

With a huge customer base of 57000+accounts spread across diverse industry verticals, Tableau is the father of data visualization software and for the right reasons! Along with having the ability to generate interactive visualizations, Tableau is relatively easy to use and offers more than generic BI solutions.

Tableau is ideal for handling vast and fast-changing datasets that are used mainly for Big Data operations, such as ML applications and AI implementations. Developers and data scientists look up to Tableau as it integrates seamlessly with high-end database solutions, including My SQL, Hadoop, SAP, Amazon AWS and Teradata. Also, a wide number of third-party resources online are on offer plus a powerful community to aid and assist new users about how to integrate the tool seamlessly with their projects.

Interested in arming yourself with the skills of Tableau? Worry not; DexLab Analytics is a top-notch Tableau training institute in the heart of Delhi excelling in many other in-demand skill training courses.

Plotly

For highly advanced and complex data visualizations, Plotly is the key. All thanks to how well it homogenizes with cutting-edge programming languages, such as Matlab, Python and R! All of them being extremely analytics oriented.

Developed above the open source d3.js visualization libraries for JavaScript, this high-valued commercial package is extremely user-friendly, along with providing inbuilt support for APIs, like Salesforce.

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QlikView

Touted as the biggest rival of Tableau, QlikView boasts of 40000 clients’ accounts across 100 countries. It is one of the most terrific players in the space of data visualization, and why not?! The customers who have used it have lauded QlikView because of its customized setup and versatile range of functionalities. However, this could also mean it takes some time to be familiar with entirely and then only it can be leveraged to its full potential.

Along with providing superior data viz capabilities, the tool excels in some of the best BI and analytics reporting capabilities. It’s simple, effective and non-clumsy user interface scores extra brownie points. Interestingly, customers use it in collaboration with its sister package, QlikSense – it manages data discovery and exploration to derive maximum benefits.

For more information on Tableau BI training courses, drop by DexLab Analytics! They are experts in everything DATA!

 

The blog has been sourced from:

www.forbes.com/sites/bernardmarr/2017/07/20/the-7-best-data-visualization-tools-in-2017/#6fdf13cf6c30
 


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3 Most Used Data Science Tools in 2018

The humongous amount of data calls for advanced data science tools – to completely understand and analyze the information.

Data analytics fuels digital transformation. The best way to do this is by arming an expert pool of statisticians, math pundits and business analysts with suitable data science tools with which they can squelch out crucial insights from the ever-growing silos of corporate data. This kind of initiatives promote a data-driven business culture, which acts as a present prerequisite – and this why here we’ve jotted down top 3 data science tools that’s weaving wonders with the new oil of the world, data:

2

Python

Both, well-performing software and a powerful programming language perfect for developing custom algorithms, Python is the most must-have tool for all data scientists. In a recent KDnuggets survey of 2052 users, Python language was recommended by 65.6% of respondents.

“We use Python both for data science and back end, which provides us with rapid development and machine learning model deployment,” shared Alexander Osipenko, lead data scientist at Cindicator Inc. “It’s also of great importance for us to ensure the security of implemented tools.”

Leslie De Jesus, innovation director and lead data scientist at Wovenware emphasized on the importance of Python libraries. “[We use] Python Libraries, including Scrapy, for web scraping and being able to extract data from the internet and upload it into a data frame for analysis,” said De Jesus.

Few others vouched for Python because of its multifaceted nature and strong optimization skills.

For Python Certification Training in Delhi, drop by DexLab Analytics.

R

Quite similar to Python, R is the go-to programming language for many data scientists and they depend on it wholly because it’s simpler and more specifically-built for data science. According to the KDnuggets poll, 48.5% respondents voted it to be one of the leading data science tools.

As for all, R programming language is blessed with cultivated capabilities for machine learning and statistics, and professionals love using it. It’s another favorite of data analysts, especially those who deals with a lot of data exploration.

“I can quickly see summary stats like mean, median and quartiles; quickly create different graphs; and create test data sets, which can be easily shared and exported to CSV format,” said Jon Krohn, chief data scientist at Untapt Inc.

Seeking R language certification in Delhi? We have DexLab Analytics for you!

Tableau

Bridging the gap between skilled data science teams and more business-oriented analytics consultants, Tableau Software is the fastest data visualization and dashboard tool. “It is a fantastic tool for data scientists and noobs working on data science,” said Pooja Pandey, senior executive for SEO at Entersoft Security. “[It’s a] quick dashboarding tool to visualize insights and analytical data with a very short learning curve.”

The lightening speed of Tableau’s visualization and reporting functions is commendable. It’s easy to learn, quick to implement and intuitive to use. Moreover, it helps different segments of a company to customize exhaustive reports according to their requirements.

Now, if you are looking for ways to hone your visualization skills, we would recommend Tableau BI training courses from DexLab Analytics. Their training courses are comprehensive, well-research and as per industry standards.

 

The blog has been sourced fromsearchbusinessanalytics.techtarget.com/feature/Data-scientists-weigh-in-5-data-science-tools-to-consider

 

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DexLab Analytics’ AUGUST OFFER: Everything You Need to Know Of

DexLab Analytics’ AUGUST OFFER: Everything You Need to Know Of

We are happy to announce that we’re rolling some good news your way – DexLab Analytics is all set to launch exhaustive modules in Deep Learning with AI starting with Artificial Neural Networks using Python, MS Excel, Dashboards, VBA Macros, Tableau BI, Visualization and Python Spark for Big Data from September 1, 2018. The course modules are on in-demand skills and they are taking the world quite by a storm.

DexLab Analytics’ AUGUST OFFER

Big data, data science and artificial intelligence are buzz words these days. More and more people are coming forward and showing keen interest on these nuanced notions that solves real-world problems. This is why we didn’t want to fall behind. We understand the importance of data in this digitized world, and accordingly have chalked out our intensive industry-ready courses.

Deep Learning and AI starting with Artificial Neural Networks using Python course module is a 30-hour long training program that gives exposure to MLP, CNN, RNN, LSTM, Theano, TensorFlow and Keras. It includes more than 8 projects out of which a couple of focuses on development of models in to Image and Text recognition. MS Excel, Dashboards and VBA Macros certification is curated by the expert consultants after combining industry expertise with academician’s knowledge. The course duration is in total of 24 hours and is conducted by seasoned professionals with more than 8 years of industry experience specific to this budding field of science.

DexLab Analytics’ August Offer is On Machine Learning & AI

DexLab Analytics’ August Offer is On Machine Learning & AI

Next, we have30-hour hands-on classroom training on Tableau BI & Visualization certification, which teaches young minds how graphical representation of data unlocks company future trends and take quicker decisions. Tableau is one of the fastest evolving BI and data visualization tool. With that in mind, we offer a learning path to all you students by framing a structured approach coupled with easy learning methodology and course curriculum.

DexLab Analytics Offers MS Excel, Dashboards and VBA Macros Certification!

DexLab Analytics Offers MS Excel, Dashboards and VBA Macros Certification!

Lastly, our Big Data with PySpark certification is another gem in the learner’s cap: the Spark Python API (PySpark) exposes users to the Spark Programming model with Python. Apache Spark is an open source and is touted as a significant big data framework for pivoting your tasks in a cluster. The main objective of this course is to teach budding programmers how to write python code using map-reduce programming model. The 40-hours hands-on classroom training will talk about Big Data, overview of Hadoop, Python, Apache Spark, Kafka, PySpark and Machine Learning.

Now, first 12 students who happen to register for each course on or before 30th August, 2018 will get alluring discount offer on the total course fee. Interesting, isn’t it? So, what are you waiting for? Go, grab all the details about AUGUST OFFER: to register, call us at +91 9315 725 902 / +91 124 450 2444 or hit the link below – www.dexlabanalytics.com/contact

 

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Difference between a Heat Map and a Tree Map

Difference between a Heat Map and a Tree Map

Are you planning to pursue a Tableau training course in Delhi? Then you must be well aware of this common confusion about the difference between these two widely used maps. There are two very useful charts which help in analyzing data, heat maps and tree maps. Heat maps and tree maps are highly insightful visualizations. However, many a times, there is a confusion between the two due to which analysts either use misuse it or totally avoid using it.

This article will help to draw a clear line between heat maps and tree maps, thus enabling analysts pursuing tableau certification, Gurgaon to create better visualizations.

We the faculty at Dexlab Analytics, the premiere Tableau Training Institute in Gurgaon aim to clarify this common doubt with this brief discussion on these two maps.

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What are heat maps?

Heat map is a type of visualization tool that is very apt to compare different categories. It helps to visualize measures against dimensions with the help of colors and size to compare one or more dimensions & up to two measures. The layout is similar to a text table with variations in values encoded as colors. In heat map, you can quickly see a wide array of information.

In a heat map, one measure can be assigned to the color and another measure can be assigned to the size.

 Quick Hands-On: Shows the sales and profit in all regions for different products category and sub-Category.

Analysis of visualization: The profit is represented by the color and ranges from red for loss to green for profit. The total sales are represented by the size.

Analysis of visualization

Hence, it is very easy to understand the performance of different products in different regions, at one glance, just by looking at the heat map.

What are tree maps?

Tree maps are a relatively new feature in Tableau, first appearing in version 8.0. The ‘tree map’ is a chart type that displays hierarchical or part-to-whole relationships via rectangles. In case of hierarchical (tree-structured) data these rectangles are nested. The space in the view is divided into rectangles that are sized and ordered by a measure. Nested rectangles mean that hierarchy levels in the data are expressed by larger rectangles (above in the hierarchy) containing smaller ones (below in the hierarchy). The rectangles in the tree map range in size from the top left corner of the chart to the bottom right corner, with the largest rectangle positioned in the top left corner and the smallest rectangle in the bottom right corner.

In a tree map 1 or more dimensions & up to 2 measures are used to create such a map.

Quick Hands- On: Show the sales and profit in all regions for different products category and Sub-Category.

Analysis of the visualization: The profit (color) and sales (size) of products are given at a Category and Sub- Category level. Bigger the size of the node, greater is the sales in that state. Similarly, the greener the node, more is the profit in that state.

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Summary: A slight disadvantage of using tree maps in Tableau is that, as the number of items increase, the amount of space allocated for each item decreases. Hence, the area available to print the labels, become small.  As a result, usually, in a tree map almost all the squares or nodes will appear blank. This defect can be overcome by providing appropriate tooltips for each node. Like in heat maps, measures can be assigned to give different   colors and sizes to the nodes in the tree map.

To learn the right use of these two maps in Tableau we recommend seeking a corporate Tableau Training in Delhi NCR for better understanding of this complex statistical application.

 

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