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Tag: Big Data and Hadoop

How Data Analytics is Reviving Up the Digital Economy

Posted on by Imarticus Learning

Today, data analytics is a booming industry. It has been estimated that the data analytics market will grow to $187 billion by 2025. These numbers are staggering and they just show how much potential this industry holds for those willing to take on it as a career.

Data analysts have an essential role in our digital economy because they dig out insights from raw data to help companies make better decisions. To succeed as a data analyst, one must be adept with programming languages such as Python, R, SAS, or SQL, among others, and know statistical analysis techniques.

Data analytics course is used to make decisions about important marketing campaigns, product development, and customer service. Data analysis techniques include descriptive statistics, inferential statistics, hypothesis testing, cluster analysis, exploratory data analysis (EDA), causal modeling, and regression modeling.

Use of Big Data and Analytics

The definition of “digital economy” has been blurred by its widespread use but in general, let’s understand what it means. The digital economy uses technology to create, capture, store, manage, transmit and exchange information. One example of this includes using a cell phone app to order food online.

Here, the companies have created an online interface for customers to easily find restaurants that deliver in their area and then order by clicking on what they want. This eliminates the need for human intervention because all orders are taken or placed through the device. This means that the entire process has become hassle-free.

Another most common example where big data is used is retail stores. They use it to analyze their customers’ shopping habits, so they know what products to put out on display during a particular time frame throughout the day. This helps them in maximizing profits while also making sure that every customer gets a personalized experience when they visit the store.

In the same way, most companies use big data to analyze and find patterns in the available data. They leverage this data to derive insights that offer a unique experience to their target group. Companies dig deeper into these insights to identify untapped business opportunities that they can explore. Companies can identify a niche and expand into that area to fill the need gap.

They also have many other options for growth, such as partnerships, joint ventures or acquisitions within their target industry verticals; these strategies allow them to survive and thrive in changing markets while often expanding business operations. While exploring new business areas, companies always study the data available to forecast the project’s profitability.

Use Case of Big Data and Data Analytics

Data analytics is an essential tool when it comes to modern marketing & growing the digital economy. Without it, a company’s decisions would be made without any data to back them up, and you could miss out on some excellent growth opportunities!

best data analytics courses in IndiaThe good news is that there are many different types of data analysis techniques available, so you can find one that works best with the kind of information you have at hand.

If this sounds like something worth investing in, you can consider enrolling for several online courses on Data Analytics from Imarticus Learning. You will learn how to analyze data yourself and come up with insights or use a computer program such as Microsoft Excel and several other data science tools to analyze data.

Conclusion

The digital economy is expanding day by day, and it might replace traditional economies in the future. Artificial intelligence (AI) powered tools manage data in this new environment, while manual tasks remain essential for understanding the numbers.

However, businesses rely heavily on consumer insights obtained through machine learning algorithms. These algorithms are decoded with the help of analysts who provide valuable input during the decision-making processes.

Marketing of the Future: How Data Analytics is Changing

Posted on by Imarticus Learning

The corporate industry is ever-evolving, and even more so when it comes to data analytics. From standard out-of-the-box reports to a tool operated by digital mediums, it has come a long way. In the past, it was mostly a way to decipher and keep records of bygone trends, but now it has turned into a tool that helps you predict future trends.

It even helps you understand your target customer better through their online habits. And as daily life gets more and more virtual-oriented, the need for machine learning and AI-oriented data analytics will keep growing. So will grow the number of positions for good data analysts.

Here, you have a chance to learn data analytics with Imarticus Learning’s new PG program to enhance your skills to the max.

Coming back to the evolution of data analytics throughout the years, there are a few major changes that need to be addressed. Such as the shift to digital analytics from standard reports, as well as live AI reports and alerts.

Digital Analytics from standard reports

 The major difference that has gained traction in the last few years would be how virtualized the data analytics industry has become. In the past, most of the analysis process was done through tool-generated out-of-the-box reports which today are almost out of date. Now the main focus has shifted towards reading the targeted customer’s habits and needs and forming strategies to cater directly to it.

It becomes a lot less hassling on both parts as instead of guessing you’re actually finding out what your client needs and providing solutions for it. Now with the change in how data is extracted and processed the job of an analyst has also evolved. This is one of the reasons why data analytics courses in India have been getting more and more popular in recent years.

 Live AI reports and alerts

 Another system that has become immensely popular is live AI reports that alert the clients to any ups and downs in trends. This helps them to develop quick strategies to respond to the changing trends. Not just that, the sources from which data is generated have changed drastically. Not just real-time market trends, data today can be sourced from online retails, social media, intelligence tools as well as pop-ups and advertising platforms.

The bandwidth of data has increased and along with it, the variety, responsibility, and positions of a data analyst job. As this process evolves more the scopes will increase even more in numbers. This is a good time to enhance your skills if you are thinking about career prospects. There are many institutes that offer good data analytics courses in India that might suit your preference. However, there are few things you should keep in mind when it comes to data analytics:

  • Many companies are venturing into exploring open-source software, but the majority is still using business analytics tools and visual analytics.
  • Data analysis has become a part of our daily lives. As a result, new and faster ways to generate data are coming out that need higher levels of skills.
  • The industry is constantly evolving, so it is necessary to always be top of your game as a data analyst.

Conclusion

Data analytics is one of the careers that has a firm base. More and more opportunities are going to open up in the future. This might be a good time to learn data analytics with a proper PG program that will help your career bloom.

What are the Big Data Use Cases That Explains Digital Transformation?

Posted on by Imarticus Learning

The business world is transforming. Big data is influencing business decisions, marketing optimizations, business predictions, and day-to-day operations. Big data is expected to reach $300 billion by 2023. Though the term ‘Digital Transformation’ is loosely used as a euphemism for the modernization of data infrastructure, the true meaning of the word is becoming vital for the business world.

big data analytics courses in IndiaIt is true that the organizations are increasingly becoming data-centric, that they allot nearly 40 percent of their technology budget for digital transformation.

Data analysis courses facilitate faster, better, and smarter business decisions helping to achieve better operational efficiency, building a loyal client base, and leading to higher profit. Let us have a look at some use cases that explain this transformation.

Banking

Banks need to deal with a massive amount of financial information. Big data is used in banking to structure the collected data, organize them based on the business needs and analyze the data to derive insights on spending patterns, storing historical data like the transactions, payment records, etc. It also helps in identifying fraudulent actions and ensuring preventive measures are in place to block such frauds.

Another area of big data application is to prevent identity thefts. The banks use big data to keep a tab on customer actions. For example, if a customer follows regular spending patterns using the credit card such as groceries and general shopping, and all of a sudden there is a change in the behavior, such as spending money in gas stations and convenience stores from multiple locations across the city, the bank suspects something unusual. In this case, the bank may try to call the customer and find out if the card is stolen.

Online Shopping

Imagine you visited an online store and added some products to your cart. On second thought, you abandoned the cart and signed out without making any purchase. After some time, upon casual browsing, you see an advertisement for the same product you had planned to purchase.

The next day, you receive a mail with a discount offer for the same item. Targeted advertising is another application of big data. Online stores watch every movement of their customer from the moment they enter the store. They keep track of the pages you visited, the product you intended to buy by adding to the cart, etc. They use all this data to show targeted ads with irresistible offers that finally nudge you to purchase them.

Travel and Logistics

Big data facilitates the smooth running of logistics and transportation. It helps in scheduling flights, to show the booking status and seat availability, seasonal fluctuation in booking, etc. It also collects data regarding weather across the globe to predict flight delays. Big data is also used to analyze user trends and to predict the number of airplanes needed to cater to the increasing number of passengers. It could also be used to perform competitor analysis.

big data analytics courses in IndiaGiven above are some use cases that explain the application of big data in various industries. Apart from this, education, healthcare, digital advertising, environmental studies, human rights, etc. are some prominent areas that use big data to streamline their actions.

If you aspire to start a career in big data, this is the perfect time to enroll in a big data analyst course and secure a lucrative career.

How A Security Camera Vendor Exposed User Data While Performing Analytics?

Posted on by Imarticus Learning

A company responsible for manufacturing security cameras recently cost a huge number of its users their privacy as well as personal data which was accidentally exposed onto the internet. After admitting and owning up to their mistake, they went on to explain exactly what went wrong.

According to the company data belonging to users like their email address, body metrics, and IDs belonging to their WiFi networks were left exposed while critical information like financial information and the user’s passwords were left unaffected. This took place in December of 2019.

This incident occurred as a result of a misconfiguration in the database of Elasticsearch. This contained data that was generated by millions of the company’s customers, which they blamed on one of their employees. After explaining the issue, the company promised and was determined to keep looking into the database’s lack of proper security standards.

For those wondering what Elasticsearch is, it is a scalable analytics and search engine that is both open-sourced and includes full-text searches. It allows its users to analyze, look for and store large volumes of data efficiently and in real-time.

How exactly did the incident take place?

During an internal project which was meant to determine ways to measure metrics related to businesses in a more efficient manner, the incident took place. The method was to be used to measure activations of various devices, failed connections, and so on. This, however, would require data replications from the main or original production servers and into a database that would be more flexible.

This would make it easier to query. Bigger volumes of queries may possibly impact the customer’s product experience if it is done on the central database as it is very compute-intensive. Processing without there being any system lag required an individual data subset to be moved into a database that was different.

In doing so the user data was exposed in an unencrypted manner while it was being transferred to a novel database for querying. An employee had cleared out all prior made security protocols due to an error that led to the unfortunate incident. The new database only held a data subset and did not include any government-regulated or vital data such as passwords and financial intel.

What was exposed to the web exactly?

Until now, the company has only owned up to exposing the data which has been revealed and denies any evidence of data breaches. The company informed the public about the customer data that had been exposed which included data from their artificial intelligence assistants like Alexa, data pertaining to their health, their email addresses, and IDs to the networks of their Wifi’s.

Users have been asked to be careful against possible phishing ambushes because hackers could possibly have access to their user names and email addresses. These could still potentially be used to thieve credit and financial information.

The company also claimed that there was no evidence of exposure to their tokens required to log in. Users, however, have been logged out of their accounts as a precautionary or safety measure, allowing new tokens to be generated for logging in. The company has been working towards ramping up its security. This may include the addition of a two-factor method for user authentication. For aspirants looking to know more about the world of data science, a data analytics course would be perfect.

best Data Analytics courses in India Not only would allow aspirants to learn more about the field but it would also equip them with all the necessary information and tools required to succeed in a data analytics career.

How does Data Analytics help to Detect, Assess and Prevent Fraud in 2021?

Posted on by Imarticus Learning

Fraud is a major problem in today’s digital world. Whether it is data analytics or data sciences, data analytics has become an integral component of fraud prevention. Data analytics is the process of data manipulation to identify patterns and predict trends based on data sets. The data can be in various formats like text, audio, video, images, or even data generated by sensors.

data analytics coursesIn simple words, data analytics is a data-driven approach to help you make better decisions. It helps organizations detect, assess, and prevent fraud in 2021. Data analytics courses are the latest trend among MBA students because data is so important to every aspect of life today.

This blog post will discuss how data analytics can help us detect, assess, and prevent fraud in 2021!

How does Data analytics help to detect, assess and prevent fraud in 2021?

In today’s data-driven world, data analytics has become an integral part of financial services. While data is not new to the industry, collecting and processing it at scale did pose a number of challenges in past years. However, with advancements in technology and data storage capabilities, data analytics as a tool for fraud detection has gained prominence within banks, especially after the 2008 economic meltdown.

Nowadays, organizations are generating large amounts of structured/unstructured data from various sources like customer service calls, social media platforms, etc., which can be analyzed using tools like machine learning, artificial intelligence (AI), predictive modeling, or deep learning algorithms, among others to predict potential threats on their business operations including risk management strategy thereby reducing operational costs & improving profitability by increasing revenue streams through better data-driven decisions.

However, data analytics is not just about data storage and analysis of unstructured data to identify anomalies within the data sets; it also focuses on methods that can be used by organizations to prevent frauds in real-time – a key area where financial institutions are looking at for growth opportunities as demand from millennial customers increases for mobile banking and increased online transactions via e-commerce portals among other channels.

In order to support their digital transformation journey & build a robust risk management strategy, banks and other institutions have started investing heavily into analytics capabilities by hiring data scientists and data analysts to leverage the power of data for fraud detection in real-time.

According to a recent report by MarketsandMarkets, the global data analytics market was valued at $16.06 billion in 2016 is expected to reach $73.47 billion by 2021, growing at a CAGR of 28% during the forecast period from 2017-2021.

Some key areas where data analytics is being used extensively include: 

Customer profiling– understanding customer behavior patterns using unstructured data sets such as social media posts or email communication logs;

Fraud Detection– monitoring transactions on data sources across data systems and data formats to identify suspicious activity;

Risk Assessment– showing the correlations among data sets of different entities within an organization or between organizations.

This is a great opportunity for anyone who wants to learn data analytics, as there are plenty of job opportunities for data specialists.

Learn data analytics with Imarticus Learning

Imarticus Learning offers data analytics courses in India that help professionals from diverse backgrounds understand concepts of data analysis. This course enables you to analyze large amounts of data using various methods such as statistical tools, pattern recognition, etc.

data analytics courses

Thus, you’ll be able to solve complex problems related to web intelligence, predictive modeling & simulation techniques or extract information quickly with minimal time lag through the Business Analytics course.

For more insight, connect with us through the Live Chat Support system or visit any of our training centers based in – Chennai, Mumbai, Thane, Pune, Bengaluru Hyderabad, Delhi, and Gurgaon.

Analytics & Sports – How Data Analysts Be Asking in The Glory in The Sports

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Sports have seen their fair share of analysts and pundits ever since the first game was played. Traditionally, the analysis made by these pundits and analysts is based on hunches rather than concrete mathematical and statistical foundations. Even if they tried to factor in the statistics, there is no way that a human brain would calculate the entire complex, behind the scene calculation, which goes into a typical mathematical or statistical model.

So, it was thought that data analytics in the sector of sports had reached saturation. It all changed with Machine Learning and Artificial Intelligence.

In case you are not aware, machine learning and artificial intelligence are the fields that employ complex statistical models with a colossal amount of data to analyze the data, derive insights, and make predictions from it. So, when these advanced modeling techniques are fed the data generated from sports, we derive more accurate results, wisdom, and forecasts than all the pundits and legacy sports analysts.

Let us now see precisely what makes data analysis so lucrative in this sector.

How is sports analytics changing the paradigm?

There are only two ways in which sports analysis is being used in today’s paradigm. One is when the sports teams ask for data analytics, and the second is when it is used for sports betting.

data analytics certification course in IndiaThe first step of the Data Analytics course in sports involves mining various data like stats of any individual player, match conditions, and the teams’ recent performances. Then, all the information is passed down to Data Analysts.

It is their job to run machine learning models on this data to generate new insights. Now, these insights could be as simple as whether the team would win the next match or not.

To something more specific like, will Ronaldo be able to score his third goal with his left foot in the 69th minute?

Analytics is not limited to in-game events. By analysis of the data generated by the fans, the team would be able to cater to their needs better and thus improve their following. The sports team can also use data analysis to enhance merch sales.

How are big teams using data analytics?

While there are many examples available out there, we choose the ones from football.

Manchester United: We all have seen the Red Devils wear the AON branded shirts for a long time now. ManU has been using AON’s data analysis to stay ahead of the curve.

Real Madrid: This might come as a surprise to many, but Real Madrid has partnered with Microsoft (the Azure platform owner) to provide the Madridistas with all the analytics they need. They use Microsoft services to plan out the training, performance, and even fitness regimes of their players.

Conclusion:

There are a lot of apparent benefits when it comes to using data analytics training in the paradigm of sports. We have barely touched the surface here. However, we hope that we were able to provide you with some new information about data analysis in sports today.

Data Analytics in Healthcare: Can a Techie Succeed in The World of Medicine?

Posted on by Imarticus Learning

In the modern-day, Information Technology has seeped into all sectors. Industries have adopted Data Science and Analytics to drive their work and have reaped the rewards for it. In the paradigm where Data Analysts are highly sought after in all sectors, how do they fare in the field of Healthcare?

 

Big Data Analytics courses are the perfect way for techies to break into the medical sector. It has become a tool with unlimited potential, and a Data Analytics career in healthcare is a very real and prospective opportunity.

Data Analytics is generally used to draw meaningful interpretations, find trends and predict possible outcomes from Data.

Healthcare Analytics specifically aids in avoiding preventable diseases, conducting an accurate diagnosis, predicting and combating epidemics and coming up with effective treatment strategies for diseases.

A Healthcare Analyst contributes to improving the quality of healthcare and reducing the treatment costs by automating tedious processes.

Applications of Data Analytics in Healthcare

There are many applications of Data Analytics in healthcare, and a career in the field works to implement these uses. Some of the most popular applications are:

Patients’ prediction: Healthcare Analytics can be leveraged to improve patient predictions. The past admission records can be used to discover hospitalization trends, peak times and deploy personnel accordingly.

Strategic Planning: The existing data can be used to identify patterns, conduct studies and map out strategies for extensive care and in community medicine.

Electronic Health Records:

It is one of the most popular uses of Data Analytics in Healthcare. It is used to track patient medications, treatments, progress, and medical history. Data Analytics on these can reveal more details about their medical conditions and lead to more accurate prognoses.

Predictive Analytics: Predictive Analytics is the practice of recognizing patterns and predicting probable outcomes by studying the data presently available. This can be used to improve care delivery for patients with complex medical history by using history to try and predetermine the conditions they may face in the future.

Data Analytics Careers in Healthcare

The applications of Big Data analytics in medicine are vast, and more are being uncovered every day. In this scenario, techies are being welcomed into the sector with open arms. Healthcare employs techies as Data Analysts, Informatics Consultants, Clinical Data Managers in the Quality and Performance improvement sector.

One can also get promoted to leadership positions for other Analysts as Informatics Director or Chief Medical Information Officers. All these positions come with their responsibilities as well as perks. The roles and responsibilities would also entail assistance in the proper integration of data analytics within specific healthcare areas.

Conclusion

A career as a healthcare analyst is a door that opens infinite possibilities. Not only do you get to save lives as a part of the field, but you also get to innovate and change medicine in your way.

What Is a Real-time Processing in a Big Data Use Case?

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Breaking down Real-time Processing

In today’s digital era, people are accustomed to real-time information that helps them make more informed decisions by factoring in the latest updates. Businesses in contemporary need real-time information to remain competitive in the market and improve their offerings.

best Data Analytics courses in IndiaLeveraging big data has become indispensable for businesses as it helps them provide valuable insights into the market. A big data career is also considered one of the most sought-after career choices given the demand for the same.

Real-time data processing systems help to factor in rapidly changing variables and relevant data to provide instant output so that any unnecessary delays can be avoided.

Some of the most prominent examples of real-time processing include order management for e-commerce websites, online ticket booking, financial fraud detection, radar range system, etc. A continuous stream of data is required to produce instant output in real-time. The most prominent benefit of real-time processing is that it helps to provide instant results and ensures that everything is up to date.

Real-time Big Data Processing Applications

Some of the most prominent applications of real-time big data processing in the contemporary include the following.

Online Commerce

Online commerce or e-commerce platforms heavily rely on real-time big data processing given the nature of business. It helps to solve issues related to customer service, inventory management, purchase pattern detection, personalized offerings, reduction of churn rate, etc. E-commerce companies also use real-time data processing to improve their logistics; they identify the nearest warehouse to effectively reduce delivery rates. It also helps to optimise the price and increase the sales volume by analyzing tons of data in real-time.

Social Media Networks

Gone are the days where people used to receive news the next day after the occurrence of a particular event. Social media networks have improved the flow of information and one can instantly receive any new update in real-time avoiding any delay in communication. Given the flow of information on social media platforms, real-time processing of data is almost a necessity. Some of the important functions performed by real-time data processing in the case of social media networks include classification of user-generated data or content, speeds up real-time trending, server functionality analysis, etc.

Healthcare

The healthcare industry also heavily relies on the use of real-time data processing systems. Some of the most common applications in this sector include real-time patient monitoring to assess crucial changes, wearable sensors and devices help to make life-saving decisions using real-time data. A majority of the data in the healthcare domain is usually unstructured and real-time big data processing helps to provide a detailed overview. It also assists in prescribing relevant medicines and avoids any unnecessary expenses.

Conclusion

Real-time big data processing has become popular in the last decade and is almost a necessity for a business that wants to create a sustainable brand in the long term.

best data analytics certification courses in IndiaThe big data career is also gaining traction with the growing demand for data analysts who can assist in the real-time processing of big data.

One can opt for data science courses from reputed institutions like Imarticus Learning to boost their job prospects and build a career in this field.

Mining and Visualizing Data: Important Skill required in Data Analytics

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Data analytics is one of the fastest-growing fields in today’s business landscape. Data analysts across industries are being tasked with data mining and visualization for different purposes like data interpretation, data analysis, etc.

data analytics certification course in IndiaAs a result of this, there’s a high demand for professionals with the data analytical skillset. There are data analytics courses that teach you data mining and data visualization.

These skills are indispensable in the data analytics landscape. If you want to be successful, it is absolutely necessary to learn this skill set.

In this blog post, we will talk about the important skills required for data mining & visualization and how to find a good data analytics course that offers them!

Key skills required for data mining and data visualizing

As a data analytics specialists, important skills you must have to apply for data mining & data visualizing jobs are:

Data Mining: Evaluating data to determine what kind of information it has and how a particular data can be used for various purposes (i.e., analysis). To analyze the data that you want to extract from a database or spreadsheet, tools like SQL queries help find specific patterns within large sets of data. You need to know about the kinds of algorithms available such as linear regression for analyzing relationships between variables recorded over time or clustering techniques applied when investigating groupings in your data set.

Data Visualization: Achieving insights into complex datasets with accurate representation through graphs, charts, etc. This includes designing insightful visualizations without sacrificing data accuracy. For this, you must have knowledge of data visualization techniques like data smoothing to make data trends more visible or data clustering for creating informative thematic maps.

Data Analytics: The application of statistical analysis to data in order to reveal patterns and trends that can be used for decision making, modeling future data, etc. For this, you need knowledge about the various analytical techniques like linear regression or time series forecasting, which are then applied to data sets in order to make predictions with mathematical models.

Understanding these important skills will help you think critically and understand how data analytics is done!

How to find a good data analytics course?

– The course should teach data mining, visualization, and advanced SQL skills.

– It should also have a good rating and be well-reviewed by existing students.

– A course with thorough programming exercises is preferable to one that just offers lectures or videos.

– The institution needs to provide a certificate of completion for the student in order for them to become certified data analysts, as many institutes are providing the courses without any certification.

If you are looking for a data analytics course that has all the above-mentioned features, then Imarticus Learning is for you!

A Rewarding Data Analysts Career with Imarticus!

best data analytics certification courses in IndiaKnowing the need for new-age careers & the potential of online education, Imarticus offers certification courses in data analytics for beginners and advanced levels.

If you want to further your career in data mining & to visualize data, and have a leg up over other applicants, getting a certification in data analytics is your best option. An advanced degree with various specializations at Imarticus will add credibility to your profile and position you as an efficient professional.

For any further details, contact us through the Live Chat Support system or visit any of our training centers in Mumbai, Thane, Pune, Bengaluru, Chennai, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Most Essential Asset for Professionals: Data Analytics Tools!

Posted on by Imarticus Learning

To perform data analysis, professionals use tools & software that ensure the best results. There are many of them in the market, but a few are on the top list for data analysts that need to be chosen wisely to extract the best benefit. 

This article discovers the best data analyst tools and highlights key features of each based on different types of analysis processes. But first, here’s a basic definition & introduction.

What Are Data Analyst Tools?

Data analyst tools are applications & software that data analysts develop & perform analytical processes to make better, informed business decisions while keeping costs low & profits high.

Top Tools Used by Data Analysts?

1. Business Intelligence Tools

BI tools are the most represented means to perform data analysis. Specialized in business analytics, they prove beneficial for every data analyst to monitor, analyze, and report essential findings. Self-service, advanced SQL modes, and predictive analytics make them easily adjustable to every level of knowledge without immense IT involvement. 

DATAPINE covers most requirements from beginners & advanced users.

Key Features:

  • Visual drag-&-drop interface
  • Powerful predictive analytics & interactive charts & dashboards
  • Intelligent alarms triggered for anomaly

2. Statistical Analysis Tools

There exist multiple programming languages that make work easier & effective. With the expansion of languages, some rules and scenarios need special attention for statistical data analysis & modeling.

R PROGRAMMING is the most popular tool for data analysts.

Key Features:

  • An ecosystem of more than 10k packages & extensions for data analysis
  • Statistical analysis, modeling, & hypothesis testing
  • Active community of researchers, statisticians, & scientists

3. General-Purpose Programming Languages

Programming languages help to resolve a variety of data problems. Tools like C#, Java, PHP, Julia, Ruby, and Python are many reliable solutions.

PYTHON is the most trusted tool.

Key Features:

  • Open-source solution with simple coding processes
  • Easy integration with other languages
  • Advanced analysis processes through ML & text mining

4. SQL Consoles

SQL is a programming language used to manage data held in relational databases, effectively handling structured data for analysts. Highly popular in the data science community, these tools are used in various business cases & data scenarios. 

MYSQL WORKBENCH is the most popular one.

Key Features:

  • Unified visual tool for data modeling, administration, SQL development, backup, etc.
  • Instant access to the database via Object Browser
  • SQL Editor offers color syntax highlighting, reuse of SQL snippets, & execution history

5. Unique Predictive Analytics Tools

Predictive analytics is an advanced technique to combine data mining, AI/ML, and predictive modeling to predict future events. It is an essential data analysis tool as it simplifies predictive analytics processes. 

SAS FORECASTING is an analysis software helpful for predictive analytics processes & helps analysts to predict future scenarios.

Key Features:

  • Automatic forecasting for entities or products, including hierarchical forecasting
  • Scalability & modeling to create an ensemble
  • An unlimited model repository including time-series & casual methods

Apart from the tools mentioned above, there are industry-specific analytics tools & data science platforms that assist professionals. A business analytics course can help you better understand what data analytics is!

Build New-Age Career with Imarticus:

data analytics coursesImarticus Learning offers Data Science Courses, the most extensive, industry-approved experiential learning program ideal for Data Analysts. 

Industry experts have developed the programs to help students learn real-world applications of Data Science from scratch & build robust models to generate valuable business insights and predictions.

Take a giant career leap with this analytics program.

For more details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.