In today's data-intensive market landscape, analytics plays a significant role in keeping a business agile and competitive. Financial analytics is one key area that enables organizations across industries to truly predict the future of their strategies and goals, and take mindful decisions that can foster their growth.

Better insights into financial efficiency measures, operational KPIs, product / service and customer profitability and enable businesses to augment revenues and the value of shareholders. They also help in overcoming any related shortcomings and modify their approach to meet their customer's needs and ensure superior end-user experience.

In this article, you will get to know about some of the key financial analytics that every organization, irrespective of its shape and size, should work with:

Predictive Sales Analytics (PSA): It goes without saying that sales revenue is the backbone of any organization. So, implementing strategies to know how much growth your business can expect in the current and following years can have a strategic impact on your business's bottom-line. Here, predictive sales analytics applications come handy. It enables you to evaluate how effective your forecast is, and also, to augment your sales pipeline in approaching years. Organizations making use of PSA tend to adopt an array of competencies and tactical approaches to gain learning about their customers.

There are two sure-fire ways to estimate sales – comparing past trends with the current and making use of predictive techniques, such as correlation analysis. PSA is considered as a powerful tool for planning and achieving Hassle-free workflow by enabling clients' to manage their respective operations in an effective way.

To put it simply, let us say, you have done predictive analysis and you have figured that in a certain month of a year, your sale may drop. In this case, you can implement new and effective strategies to boost sales for that particular period. Having a clear idea about your sales generation will stop you from falling in panic situations. According to studies, conducted by leading research institutions, forecasting how productive your business will be in the months or years to come keeps your business abreast of all ifs and buts, giving you a platform to thrive.

Product Profitability Analytics (PPA): To give a strong competition and make the best out of your investments, it is important to comprehend where exactly to invest. In order to calculate the profit, you will need to look at your product and its costs separately, and for sure, this could be a difficult and time-consuming task.

Here, PPA is a top-notch solution that helps determine profit-line on the basis of each product. It enables you to gain quick insights across all your offers so that you can make an informed decision for your business. For example, if you get to know what products customers demand the most, then you can promote those products strategically.

Customer Profitability Analytics (CPA): Be it a cloud hosting provider, a giant e-commerce platform, or just any business working on the World Wide Web , having a clear data about who your potential customers are is always sage. A fair comparison between profitable and non-profitable clients helps in doubling the revenue generation. Remember, there are two kinds of customers – one that brings value to your organization, and the other one that brings risk to your organization. Extracting this detailed information about the customers will the best complement for your future marketing efforts.

The best thing is this you can do it with the help of CPA as it smoothly enables you to analyze the behavior of customers of both kinds.

Shareholder Value Analytics (SVA): How successful your strategies are will be determined by the interpretation of the final outputs evaluated by media, experts, stakeholders, and shareholders. SVA helps in adjudging the business value on the grounds of what returns a business provides to its stockholders. It also determines the percentage of risk and value delivered to the shareholders. That's why most of the experts recommended completing SVA with profit and revenue analytics for better comprehension and execution.

Cash Flow Analytics (CFA): You need fuel to drive your car, do not you? In the similar context, your business needs capital to operate. Predicting inflow and outflow of capital is important to ensure the health of your business. Herein, CFA and regression analysis tools can help in determining how much capital you may need for future investment. This is not where the CFA benefits end up. Managing cash flow and foster corporate functions also fall under its responsibilities.

Adding more to it, it always proves sagacious when it comes to right predictions while taking a look at past data.

Value Driver Analytics (VDA): Only planning does not offer desired results. For that, you need to implement your well-researched strategies. On top of it, you should have a positive and pragmatic business approach. A great understanding of economic drifts that can disturb your financial motifs will help you forecast correctly and promptly. Your goals will determine your value and aid you in meeting your strategic business objectives. In connection with this, VDA will help you analyze these strategic business drivers so that the expected outcomes can be achieved. Not to forget, these drivers are majorly based on assumptions, so needs to be cross-checked.

It is important for CFOs to embrace financial analytics so that they can achieve their organizational goals. Financial analytics provides in-depth and proactive datasets that offer better insight into profit, cost, and market trends, thereby including a rewarding experience for your business.

WHY IS BUSINESS ANALYTICS IMPORTANT?
The foremost goal of any organization is profitability, and customer satisfaction is a huge component of the success of a business. When an organization innovates and holds ahead of its competition, it fulfills and goes beyond customer expectations. Many businesses still rely on ineffective, time-consuming traditional techniques for decision making processes that can not keep pace with the competition.

The use of "gut feel" in taking strategic decisions still plays an important role among business leaders. But does reliance on "Gut feeling" and "Traditional techniques" make for smart decision-making? What's the best approach?

The technology boom has given rise to innovations in how data is used. Business analytics is the solution and the best move to ensure competitiveness in today's era. To define the term: "Business analytics, one of the emerging fields in the data science, refer to the methods and various statistical and quantitative techniques used by an organization for informed decision making and business modeling".

Analytics is the change that helps you to get your business on track. It assists the businesses to convert the humongous amount of generalized data into observation, patterning and vision.

BENEFITS OF BUSINESS ANALYTICS
What was discussed above is just an academic definition. Now let's discuss why one needs to adopt it in business operations:

1. Fast decisions are easily taken, but what matters is smart decisions taken in a short period. It helps to inculcate faster and smarter decision making into business culture of your organization. With the help of business analytics, the company can empower a team for data analysis to extract targeted information. When a company accesses accurate and essential data, undoably, it will take the right decisions.
2. Analytics helps in quantifying business values.
3. Most businesses provide training programs for fresh recruitments or older employees where the core business values ​​are reflected or refurbished. Instead, companies should go a step further and undertake the help of business analytics to translate business values ​​into numbers. This is a more cost and time efficient undertaking.

CAREER PATH OF A BUSINESS ANALYST
A business analyst is one who assists organizations in the process of business analytics. The career path of a business analyst is not strictly defined as there are several options based on industry, qualifications, interests, preferences etc.

• Training provides trainees with the skills and knowledge needed for a proper understanding and interpretation of data.
• Training courses help students in getting exposed to data systems and tools like R, SAS, Python etc. making them eligible for various analytical jobs.
• The best incentive for undergoing a course is that the industry-best average salary of a business analyst is Rs 491,522 a year. There are various skills that can increase the pay scale of a business analyst like project management, SAS etc.

CONCLUSION

• The role of a business analyst is often seen as one that bridges the gap between different departments in an organization. There are various business analytics courses which can help you achieve all the benefits mentioned above. Candidates with these skills can help an organization to strategically improve operational efficiency.

We've come quite far from our discussion on leveraged sales and by no means is it a finished topic. The next subject evolves around the importance of data analytics for leveraged sales and general business practices. For many new teams, this is a cornerstone subject matter that will help them from falling flat on their face completely. If you're a harden veteran but need an update for your business this should keep you moving forward or get you out of the mud.

Leveraged Sales are based on performance and NOT luck

Leveraged sales are measured and not just by the sales. They must be measured by views, click through, visits, bounce rates and time on page. The content that defines the product is also examined, especially the call for action, the design and graphics play an immense role. So, this is why it's not based on luck and anyone that is not measuring their general business and products may not see the success they desire. Each of these can be set up in an analytics program and trimmed for a report that can be examined anytime.

Leveraged sales performance must ride with the promotional element. The more that you promote your business, the more chances that your ideal prospect will visit your product page. The more views and hits on your product page will increase the chance for a direct sale. In order to achieve the results, the promotional aspect must be balanced. Like a Samurai, it must be strong and wise at the same time. It may also be confidential like a rose but strong enough to pull attention from the other distractions online. So, your performance level can increase if it is well maintained and acted upon by the audience.

Build an incredible story and the world will come

Every leveraged sales product has a story that precedes it. It is your business story that sets the stage for your audience. If the story is to be successful, one must contemplate the need for the story. The owner must forge it over from the furnace of their experiences and shape it into one that is deliverable and copy proof. It takes talent to be original, there are too many copy cats on the market today. Put in the effort to write the story and use analytics to achieve your goals. Do not copy someone, be unique and blaze your own path to glory.

Data analytics, as a professional skill has come about in so much demand in the last 8-9 years as a result of the capabilities of companies all over the world being able to capture the customers data relating to how to purchase or how the company manages its own financials. Evolution in software development has enabled this capacity. However, there is this constant debate around whether or not the same software tools used to create the data capturing capabilities can be used for data analysis tools to achieve the same.

One such tool is the SQL based database software, which essentially forms the backend for any operation. It is used to perform queries to get information from data sources. Audit Command Language is another tool, which is dedicated for only data analytics projects. Let us see the major differences between these tools, to settle which approach is better.

1. Easier Interface – The first advantage of ACL over SQL based tools is the user interface. For any end-user trying to work on some analytics project, they can very well complete basic routine tasks to get to some very insightful reports by simply using the GUI. Please see demo of ACL GUI below:

2. Workspaces – One defining feature of the ACL tool is the "workspaces". Workspaces allow the end-user to write simple lines of code for data manipulations and test the results without having to actually run any scripts. The workspaces allow the flexibility and another layer to the design process of the ACL project to execute the desired tasks.

3. Scripting – Scripting in ACL Audit Command Language is a combination of scripts and workspaces. most data manipulation tasks like creation of new formatted fields from the raw data are mostly performed in the workspaces, where the syntax for scripting is fairly simple. Other than workspaces, most tasks (such as summarizing, filtering, sorting etc.) data can be performed simply by using the GUI provided by the tool. If any user is inclined to learn how to script (with respect to analytics tasks like summarizing, sorting, appending, joins etc.), the logs give the scripts related to all such tasks performed using the GUI.

ACL Audit Command Language can be considered an entry-level skill that can be used for almost any kind of analytics projects especially, in the audit / risk analytics domains. It acts a refined layer of software on top of the data captured in ERP systems. It is easier to catch on for professionals who do not have a technical background and almost takes like a day maybe, if you have a technical educational background. For these reasons, it is easier to train a work on this tool, because of the easy learning curve and the relatively affordable investment as compared to SQL, SAS, HADOOP / HIVE infrastructure.

Are you looking for a career as an analyst? If you are really interested in finding your perfect job as an analyst you’ve come to the right place. You will get world-class training and 100% placement opportunities for internships and jobs in this course. You can complete the coursework in the comfort of your home via distance learning. The utilization of distance learning is of great importance in enhancing your skills and knowledge as an analyst.

ABOUT ANALYTICS CERTIFICATE COURSE-

The duration of the analytics certification course is about 160 hours of classroom training on different certificate courses such as Business Analytics, Data Analytics, Data Scientist, etc. The training is lead by extremely qualified professionals with years of experience in this field. Moreover, the emphasis is put on practical training rather than on theoretical training since this is more in line with what the jobs involve. Enhancing your skills and teaching modern techniques is the ultimate aim of professionals.

BRIEF DESCRIPTION ABOUT COURSES-

1) BUSINESS ANALYTICS– This course is drafted by experts with attention to the demands of professionals who want to pursue their career in this field. Business analytics uses statistical analysis and statistical techniques to forecast the conditions of the market and how it will affect business activities. The job of a business analyst is to determine the current trend and its influence on the business environment as well as to predict the future trends and ways to take maximum advantage of those trends. In the current scenario, it is one of the best career options because of the huge demand from business organizations.

2) DATA ANALYTICS– It is divided into two categories-a) quantitative data analysis b) qualitative data analysis. The former focuses on statistical and numerical data while the latter focuses on non-numerical data. It is a process of collecting data from various sources and integrating them so as to determine the best solution.

3) DATA SCIENTIST– In this course, students are trained in using data analysis tools, equipment and various software for data mining and data optimization. The job of the data scientist is to determine the best solution among the available choices. It involves going through a series of processes before making the final decision. The first step is collecting the data, the next is performing data mining and doing statistical analysis and forecasting using the data.

BRACE YOURSELF FOR OCEAN OF OPPORTUNITIES-

Students are trained by renowned professors with the best knowledge in this field. A 24-hour 7- day-a-week e-learning facility is provided to students along with other online study materials. There is an e-portal on the website on which students can post their questions and have discussions with professionals. After completion of the course there is a placement program available where students are provided with on-the-job training, case studies, live projects and internships. This career option is trending among students not only because of the stable income but because it is also one of the most preferred white-collar jobs.

Running a business can be a tricky affair. Running an industry successfully requires an outstanding amount of analytical training and observation. An exceptionally calculated and planned approach towards business can make a huge difference in the sales, resulting in profits. To carry out this analysis, access to the necessary data is essentials. Deciphering the data can certainly benefit the business in making big profits. To gather this massive amount of information many enterprises use the automation tools and sophisticated software. According to the CEO of a prominent e-commerce organization, right usage of data ensures the products are developed and marketed according to the customer requirement. It guarantees a more significant success rate for the business and the overall development of the coming.

What is Business Analytics?

It is a form of commercial planning which uses earlier data and customer patterns to form the marketing objectives of the trade. It focuses on making new insights regarding the issues faces y the organization in the previous point of time. Also, attempts to reevaluate the methods, to fix those problems. According to the best schools providing Business Analytics training, with the help of data and statistics, on can create better products for the customers.

According to top schools, providing Business Analytics training in, the subject can be used in the following ways to improve the profits of the industry:

1. Better services: Using the commerce analytics, the organization can predict the customer trends and behavior. It can help the industry in improving their services.The examination of the customer data ensures, the companies can meet the commitments made to the customers. In the long run, this can help in forming a satisfied customer base.
2. Can complete the orders on time : For making sales, it is essential for the commercial organization to complete the order on times and delivery them to their location. It has to be done in the stipulated time. A delay in supplying the products means the company failed to make the required sales in the assigned time, leading to losses. With the help of automation tools, the organization can quickly identify the delaying agents and take appropriate steps to get rid of them.
3. Better customer handling : Including the sophisticated tools while planning, the companies can understand the requirements of the customers, and design products according to it. Also, the firms can identify the recurring customers who are more likely to do industry with the organization.
4. Bringing down overall cost : With the systematic help tools, the companies can get a necessary estimate regarding the essential and frivolous expenses. With such differentiation, the companies can cut down the overall cost of production.

Using the appropriate tools and techniques, the companies can bring down the cost of production and make more customer-oriented products. It guarantees the companies make a substantial amount of profits and have a better customer base. A better investigation concerning cost and resource allocation means better results for the performance of the organization.

Sports as we know it today has come a long way. There were times when watching sports on television was considered a massive step forward in terms of technology. Fast forward 60 years, watching sports on television has become the most basic thing. Today we watch sports on the go on our mobile phones or any device with a screen and internet connectivity. Proud of how far we’ve come, aren’t we? Hopefully I can change your opinion on that by the end of this article.

What is sports all about? Sports is a bunch of people getting together to play a game with pre defined rules and a referee to ensure that these rules are adhered to during the passage of play. I am a sport lover and play sports all time. My love for tennis and soccer in particular cannot be defined. My issue when it came to technology and advanced analytics was with the game of soccer in particular. Soccer is such a beautiful game. The strategies that the coaching staff come up with and the way it is executed on field by the players, it actually is a thing of beauty. I was a soccer player myself (just an average one at that) and have been part of various teams. I know firsthand how strategies are built, how much thought goes into one single run of play.

Enter -> Advanced Analytics

Most of you would’ve seen the movie Moneyball. The movie was based on the book Michael Lewis wrote in 2003. It talks about how a jock turned luminary uses advanced statistics to gain a competitive edge over his better funded opponents. This book brought about a revolution is sports. Fans and boards of soccer clubs didn’t want to settle for subpar statistics or analytics anymore. What Moneyball did is, it took an old cliché – “sports are businesses” and made us move on to the next logical question – “how do we do things smarter?”

Now let’s talk about advanced analytics. Advanced analytics in today’s world plays a massive role in every business sector. Advanced analytics has been a boon for us. Moving from descriptive analytics to prescriptive analytics, we actually have come a long way. In various businesses, where the requirement is demanding, advanced analytics are of utmost importance.

When we look at soccer, its a game that does not require too much machine intelligence, it is a game that needs the human element. When you bring in analytics and technology and try to reduce the human element in the sports, it simply just crushes the spirit of the game.

Relying on analytics heavily killed the Premier Leagues long ball game and brought in the pressing, continual passing tiki-taka. Each league for that matter had its own style of play. The Premier League had the brash and brazen style of football that was termed “The way real men play football”. There were beautiful long balls, harsh tackles but all the players just sucked it up, walked it off and it was all up to the referee on the pitch to penalize the offender or not. There were arguments and fights, the passion from the fans was crazy, that was the football that screamed of passion, when players got in the face of other players not fearing punishment. The Eric Cantona’s, the Ivan Genaro Gattuso’s, the Jaap Stam’s of the football world went missing soon enough and the diving and the biting began. Then there was the tiki-taka style of football that was played in the Spanish La Liga, the silky style of play that caught everyone off guard. The legendary Pep Guardiola and his army at Barcelona were the masters of the tiki-taka. There was Real Madrid who were always a star studded line-up with excessive parts of their play relying on lightning quick counters which most often than not left the opponents stunned. There was Manchester United who had their own brand of football being managed by the legendary Sir Alex Ferguson. That United team was a team of sheer grit and character. Each of these leagues had their own beauty and the teams had their own style of play.

When you bring in excessive technology and analytics, there emerge sorry technologies like VAR (Video Assistant Referees).

There are 3 stages as to how the VAR works:

Step 1

Incident occurs

The referee informs the VAR, or the VAR recommends to the referee that a decision/incident should be reviewed.

Step 2

Review and advice by the VAR

The video footage is reviewed by the VAR, who advises the referee via headset what the video shows.

Step 3

Decision or action is taken

The referee decides to review the video footage on the side of the field of play before taking the appropriate action/decision, or the referee accepts the information from the VAR and takes the appropriate action/decision.

Now the referee can consult with VAR for basically any doubts he wants clarified. What does this do?

• Removes the human element from the game.

• Takes up excess time and brings too many stoppages within the game, a game that was previously free flowing and continuous.

This makes it similar to Formula 1 racing. The analytics which brought about the fuel weight management systems and the numerous pit stops took the continuity out of the race and viewership reduced with the increase in technology. A pretty similar trend might occur in football if this implementation becomes mandatory.

The Positive Side of Advanced Analytics in Soccer:

Analytics are not all that bad in football. Let’s take the case of when Simon Wilson joined Manchester City in 2006. Simon Wilson was a consultant for an analytics startup called Prozone initially. He joined City to start a department of analytics and hired the best data analysts under him. He wanted to change the way how data was used by football teams. He saw that, after a defeat there was no introspection as to why they had lost and what needed to be done next time. City were a mid table club at that time. In September 2008, when the club was acquired by the Abu Dhabi United Group for Development and Investment, a private-equity outfit owned by a member of the Abu Dhabi royal family, the team suddenly found itself with the resources necessary to mount a challenge for the Premier League. Today, Wilson is Manchester City’s manager of strategic performance analysis. He has five departments under him, including the team of performance analysis, which is now led by a sports scientist named Ed Sulley.

After each match, the team’s performance data would be examined. The list is extensive. Line breaks (a rugby term), ball possession, pass success rates, ball win/loss time ratio were what used to be analyzed. “Instead of looking at a list of 50 variables we want to find five, say, that really matter for our style of play,” says Pedro Marques, a match analyst at Manchester City.

“With the right data-feeds, the algorithms will output the statistics that have a strong relationship with winning and losing.” Wilson recalls one particular period when Manchester City hadn’t scored from corners in over 22 games, so his team decided to analyze over 400 goals that were scored from corners. It was noticed that about 75 percent resulted from in-swinging corners, the type where the ball curves towards the goal. The next 12 games of the next season saw City score nine goals from corner.

Teams are investing heavily in analytics today and it is working in their favor. Look at where Manchester City are today, sitting atop the Premier League table and not being threatened at all. Look at Manchester United this season, their game has been such where their possession percentages are low but their goal conversions are high. The Manchester Derby on 7th April 2018 saw United have only 35% of the possession but they managed to trump City 3-2. Each team has their set of analysts who provide inputs as per the strength of the team.

Advanced analytics is like the coin Two Face in Batman has, “Heads you die, Tails you survive!”

It can reap crazy rewards from a team’s point of view but at the same time can disrupt the lovely game by bringing in unnecessary stoppages, replays and by taking the human element out of it. The numerous replays and the different angles, show the fans if the referee has made an error or not. Let the error happen, after all to err is human. Refereeing in soccer is not an exact science and it’s all real time. Let there be arguments about a decision, let the passion in the argument come through. Do you want to watch a football match like the El Classico or the Manchester Derby and sit with your bunch of friends and say “it was a very clean game, the best team won!” Hell NO! Don’t drive the passion out of soccer with technology and analytics. Let soccer be soccer and let technology stay away!

Definition: The Data Analytics certification is basically a certification of knowledge of general analytics, which is the understanding of how to break down a process into components from start to finish. It is also used to certify the understanding of the process used by analysts to frame a business problem analytically, allow identification of necessary data and determine the methodology for this acquisition.

Now, before proceeding further, it is necessary to further investigate the term "data analytics". What does the term data analytics mean? What is its application? Why do we need it? What are the benefits? Why do we use such terminology to describe a set of data collected? Why is it so necessary?

Data analytics:

Terminology: It is defined as the process which is used to examine certain sets of data so that results can be predicted from the information the data provides us. This is implemented with the help of certain tools which include specialized systems and software.

Reason for the terminology: The data is indeed complicated and it can be either structured, unstructured or semi-structured. With analysis, which can be done statistically using some basic scientific fundamentals, this complicated data provides us with minute information such as the amount of profit or loss the product has been able to generate, inventory levels of the product and improvisations that can be made so as to get a better exit.

The significance of the terminology: This is helpful for those industries where keeping track of the products being released is very important. The enhancement of the sales of each particular product is very important in such cases. Think of a new medicine has been released. It works for those suffering from tropical diseases and has to be marketed. The company decides to use certain methods of marketing. In order to check how well people respond to the advertising, how well the product is performing and the amount of sales generated, they need information regarding the product. This is the same for stock exchanges and trade centers.

Application of data analytics: It is used in industries and businesses where frequent updates about sales are important. There is lots of information buried in this data. It allows this information to be disclosed for the benefit of the business with improved decision making. In cases where the datasets are massive (Big Data), specific tools have been developed to manage the data. The professionals are aware of these products.

Characteristics:

· Helps in getting an analysis of the performance of the products every second.

· Helps increasing the sales.

· Helps in comparing sales.

· Helps in using various techniques and improving them.

· Gives a visual representation of how well the methods used work out.

An individual will need certified training in data analytics to perform the job of a Data Analytics professional. It will help the person to deal with Big Data and provide a correct analysis of the data being grouped. A certification will provide the individual with a lot of benefits, the primary one being employment. Ohio University, Massachusetts Institute of Technology and a majority of colleges and universities worldwide provide data analytics training and certification.

If you can’t measure the extent of something, you most likely won’t be able to improve it. When it comes to search engine optimization, measuring your traffic and reach is critical to succeeding in your venture. Google Analytics is one of the best tools you can utilise and keeps track of many things for you and even supplies live reports and traffic intake whenever you need. You simply cannot be successful without measuring your market data, as you risk only guessing the habits of your audience, and not knowing exactly what they’re looking for. In this article, we will be going through a number of ways you can boost your analytical expertise, improving your content marketing by margins.

1. Keep track habitually – Make it your top priority to check your analytics every single day. This includes checking your reports daily. Doing this ensures you are easily keeping track of what your audience is interested in, as these reports show all your top pages and numbers them into a top ten. Listing these pages allows you to see what number of traffic is leading where, and if you do this multiple times throughout the day, you can market accordingly to where your traffic is entering.

2. Understand your audience – One of the main, and best reasons, to invest in a data driven marketing strategy is to keep track of exactly who is interested in what. A well-thought marketing campaign can solidify your company or product and bring your audience closer to your brand. Using an analytical program can help you understand a number of things, such as how your audience reacts to your existing content, their favourite types of content, and their preferred method of receiving said content.

3. Aim towards non-targeted audience – This entry may seem odd, but you will understand exactly what I’m getting at if you’ve been reading thus far. We’ve stated that it’s important to understand the customer, but it is also important to understand those who aren’t interested in your product. By understanding those who aren’t interested in your product, you can tweak your campaigns to include them in your demographic, further increasing your traffic and customers.

4. Test outside of analytics – Despite this tip going against the article itself, it is still a useful and helpful method that even major companies use today. Statistics and facts can give an abundance of information on any subject, which is exactly where analytics programs come into play. But utilising other methods can be just as helpful. It can pay off to conduct surveys, or group testing towards an audience due to the fact that there can be more information put in by them. In turn, this can result in an emotional response, giving you more information than a simple analytical report could.

5. Link social engagements – Using social media can be an extremely helpful tool to use to your advantage. Facebook and Twitter are the two biggest social platforms in the industry, and if you use these to your best advantage, then your traffic will boost by massive margins. Linking the social engagements to your analytics program will allow you to keep track of all your social media posts, giving you traffic information for them as well. Using this tool to your leisure will allow you to see what is popular with your social media audience, giving you an even bigger opportunity to market to an entire different audience.

So are you looking for a certificate course from a prestigious college? Even if you can find one, there may be a problem with the location. But there is no need to worry about distance. Through e-learning you can easily glean the knowledge from professionals from the comfort of your home.

WHO ARE ANALYTICS?

In the business field, analytics are in great demand. Companies have woken up to the fact that a great deal of pertinent information is hidden in their customer data files. They are trying to hire professionals who understand how to analyze the data to provide insights that lead to better business decisions and enhanced profitability.

COURSES OFFERED BY THE UNIVERSITY

1) BASIC STATISTICS- The topics included in this discipline are Data Types, Probability, Random Variables, Graphs, Chi Distribution Technique, Central Unit Theorem, Sampling Funnel, etc.

2) HYPOTHESIS TESTING- This course includes how to formulate hypothesis statements, their uses, techniques like Parametric tests (one way ANOVA, Chi-square test, paired T-test, etc.), non-parametric tests (MANN-Whitney test, KRUSKAL-Wallis tests, etc.)

3) REGRESSION ANALYSIS- In this course, students are given knowledge of the measure and analysis of correlation coefficient, prediction intervals and confidence intervals, regression techniques like linearity, equal variance, etc.

4) FORECASTING- This discipline includes learning the strategy for forecasting, making analysis through graphs and charts, Correlogram, Methods of forecast like the Naïve method that consists of Simple and Moving average, Model-driven method that consist of quadratic, exponential, econometric models, etc.

5) DATA MINING OR MACHINE LEARNING- In this subject various topics are covered such as Matrix Algebra, Affinity Analysis, Dimension Reduction Techniques (Principal Component Analysis, Singular Value Decomposition), Supervised vs Unsupervised techniques, Pattern Mining, etc.

6) TABLEAU- In this field, students are taught how to navigate the user interface, how to access help, how to connect various data sources, how to sort and filter data and perform operations using cross-tab, creating various maps, charts and dashboards, etc.

7) PYTHON- It is software which is used to perform data mining techniques as well as regression technique.

8) DATA VISUALIZATION- The utmost importance is given in teaching three vital principles of visualization to students along with lie factor, Affordance Theory, Data-ink Ratio, Tufte’s Principal for Analytic Design and Graphical Integrity Rules.

9) MINITAB- This software is developed to perform Hypothesis testing.

10) XLMINER- This software is developed to perform various Forecasting techniques.

REDEFINE YOUR CAREER IN ANALYTICS AREA-

So if you’re planning to enhance your knowledge and gain expertise in this field, it will not only beef up your resume but will increase your chances of achieving a promising job. Training is provided by the best professionals who having years of experience and sound knowledge of the field. They focus on giving more practical knowledge related to real life problems and how to deal with them following analytic principles. The person pursuing this course must possess basic industry knowledge and learn applicable concepts to take maximum advantage of this training. The demand for analytics are growing, especially in big business companies. Moreover, the facility of e-learning can help you to gain knowledge anywhere, anytime through videos.