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Business analytics holds tremendous potential to create value for the industry and has been doing so for around two decades. Considering this, most of the business schools have introduced courses related to business analytics in their program curriculum. Some business schools have also started MBA or PG programs in Business Analytics.
As a faculty who teaches analytics courses, I have been learning from my experience and also interacting with the instructors at many business schools on how they handle the analytics courses, and how the students tend to learn these courses. I could find a few learnings in this journey and am sharing them with you through this write-up.1. Help students develop a strong foundation in mathematics, statistics, and operations research
First and foremost, it needs to be reinforced to the students that the body of knowledge in the three courses of mathematics, statistics, and operations research, is the mother of business analytics. So, the students need to have a very strong foundation in these courses to be able to appreciate business analytics in a true sense. Contrary to this, I have found many students to be thinking that business analytics is all about the programming and the tool; while it is actually about solving business problems by integrating the knowledge of business and mathematics.2. Emphasize on Solution Approach
Second, the instructors need to make the students appreciate that code is just the solution approach converted into a language that can be understood by the computer. So, the importance of understanding the solution approach cannot be undermined. This gets facilitated if the major part of the contact time with the students is spent on formulating and visualizing the problem than that spent on solving it.3. Teach analytics courses only after covering foundation in functional areas
Third, it needs to be taken care that the foundation courses in functional areas of management are thoroughly taught to the students before introducing analytics courses into the curriculum so that the students can appreciate the scope of analytics in solving business problems related to the functional areas. But, it is time that a little bit of analytics flavor is given to each course since analytics has touchpoints with every discipline. For example, in the HR course, at least a small exercise can be done on predicting employee attrition. In the corporate finance course, some exercises on risk-return modeling can be done. Similarly, in the marketing course, a small exercise on clustering or market basket analysis
can be done; while in the operations management course, some exercise on supply chain design analytics can be carried out.4. Focus on Business Applications, and cover a wide range of functional areas
Fourth, there exists a need to deliver analytics courses in a manner that focuses on the specific business applications rather than teaching the courses as pure mathematical courses. This can be done with the help of case studies. It is also important to cover the applications of business analytics in all the functional areas while delivering a generic course on business analytics. This is important for a wider variety of students to be able to appreciate what business analytics has to offer in the area of their interest.5. Adopt Hands-on Pedagogy
Fifth, hands-on pedagogy is the best approach to teaching analytics courses. There needs to be a focus on learning while doing here. When the students solve the problems themselves, they not only absorb more but are also likely to feel more confident and cool when faced with the varying versions of the problem in the industry. Here, the instructor also needs to take care that he goes to the class with a good amount of preparation, and preferably with a written code so that the syntax errors do not consume the precious class time or distract the class flow.6. Use contemporary datasets
Sixth, most of the time, the stale datasets are used in the classroom. It is obvious that if the latest datasets are taken in the classroom, the students would be able to relate more to the topic. Or, if the contemporary developments are converted into case studies, the engagement between the students and the instructor increases. The instructors need to be ready to take out time for this exercise as it requires them to prepare more for the class. Also, if the dataset is taken from a public source in the classroom, and processing is done in front of the students, the students can appreciate the end-to-end cycle of data analytics. Although there is a caveat that this may take a little more of the valuable classroom time and that the first-time data may not yield the desired learnings in the classroom.7. Encourage diverse opinions in the class
Seventh, it is important to realize that business analytics is not pure science but also an art. Therefore, diverse ways of approaching a problem, or interpreting an output generated by the software, need to be encouraged in the classroom. The students also need to be taught that there exists a trade-off between finding the perfect answer and finding the close-to-perfect answer.8. Eliminate the coding phobia among the students 9. Cover prescriptive analytics as well
Ninth, while most the business schools are covering descriptive analytics and prescriptive analytics in the course curriculum adequately, it has generally been observed that prescriptive analytics is an area that is being given lower attention. But prescriptive analytics is very important for businesses to make the best use of their scarce resources. Therefore, the students need to be given substantial exposure to prescriptive analytics at least in the functional area of their interest. For example, some portfolio optimization analytics can be done for finance students, or optimization of the marketing expenditure can be taught to marketing students. Similarly, optimization of workforce scheduling can be taught to HR students; or vehicle routing problems can be done for the operations domain. And in case the students can run a few simulations or virtual games in each of these domains before taking the analytics route, that can help them appreciate the concept of trade-offs in the prescriptive analytics much better.10. Set a strong technology flavor
Tenth, since analytics cuts across the technologies, the students need to be exposed to the basics of emerging technologies such as IoT, NLP, Cloud Computing, deep learning, blockchain, quantum computing, etc. The students also need to appreciate data mining, and there should be a good focus on teaching them to analyze the different forms of data- text and non-text, structured and unstructured.11. Leverage what industry practitioners have to offer
Eleventh, the industry sessions also need to be organized in the analytics courses. This is because the practical challenges related to problem identification, data collection, data cleaning, data processing, and drawing insights can be explained in the classroom best by the industry practitioners who are working as data scientists, business analysts, business strategists, or management consultants in the field. Also, their help needs to be taken in the design and review of the curricula. There is a relatively stronger need to appoint Professors of Practice, (as the management institutions call it), in the area of business analytics than in other areas.12. Handhold your students when they do it themselves
Twelfth, it has been observed that the students face many challenges when they try out the stuff. They may get errors due to improper syntax, or because some packages have not been installed. The instructor or a co-instructor needs to be available to them at that time, to facilitate the learning journey of the
students. The teaching assistants may help the students in debugging their codes, helping them with the necessary libraries, or explaining the code at a micro level to them.13. Try using engineered datasets where possible
Thirteenth, the well-engineered datasets that have been designed to make learning more spontaneous and can generate multiple insights when minor changes are done in the data, can be very helpful. So, the instructor should make some pre-planned changes to the dataset and show to the students the impact on the solution, which can trigger a discussion on what that change in the data led to that impact.14. Evaluate the students on application and skill more than anything else
Fourteenth, the evaluation components in an analytics course should be far from theory, and should rather check the ability of the students to apply the concepts. Although there can be some theory questions as part of a broader numerical question so that they complement the quantitative problem solving15. Help the students visualize the data, and teach aesthetics of data visualization and communication
Fifteenth, visualization of data is an important element in the classroom. Before the students start working on a piece of data, if they can be asked to visualize that data through some graphical or pictorial representations, that can be very helpful for them to understand the problem-solving approach. Also, many a time, telling the storyline through the data can be very useful, and catchy if one has to deliver a business presentation to one’s client or manager. Therefore, the students need to be taught how to create dashboards, and how to draw smart visualizations, that can make the absorption by the audience easier.16. Expose your students to a variety of software tools, but do not emphasize the tool too much
Sixteenth, the instructors should try to use a variety of tools in the classroom, so that the students can become comfortable with multiple tools. For example, if some exercises can be done on R Studio, some on Python, and some on SPSS in a course, that can make the students comfortable with a wider variety of tools, which is necessary. However, at the same time, the tool need not be given as much attention as the process of framing insights from the data.17. Do not limit your delivery to structured data or numeric data only
Seventeenth, every analytics course should cover some content on unstructured data or text data as well. This is because, in today’s context, unstructured data is enormous due to the digitization of business processes. So, in any area of management, unstructured data can be worked upon to generate useful insights.18. Start the classroom session with a problem statement
Eighteen, the problem-statement-based approach has been found to work well in the analytics courses. It has been observed that if the class starts with a practical problem statement, followed by an explanation of the theory in the process of solving that problem, the absorption level of the students is higher than that in the case when the class starts with theoretical concepts.19. Ignite the scholarly passion among the students
Nineteen, it is the responsibility of the instructors to ignite the scholarly passion among the students. For this, the depth of the topics covered should be significant. For example, while teaching regression, the students can be taught all the aspects of it, including the assumptions of regression, detecting and treating the outliers, handling multi-collinearity, handling heteroscedasticity, regression using machine learning, L2 normalization, panel regression, etc. The students also need to be encouraged to try some innovations to the model taught by the instructor in the classroom.20. Develop ethics and integrity among the budding data analysts
Last but not the least, modern-day data scientists need to exercise ethics to the highest level while doing their studies and publishing the findings. Therefore, the students need to know how they can maintain objectivity in their study and not let the results or findings be influenced by their personal biases and opinions.
Thus, it can be seen that the institutions have an important role to play in the process of ensuring that business analytics as a course is taught not only in letters but also in the spirit. If this role is played adequately, the fresh graduates coming out of the business schools can be good data-driven decision-makers by the time they graduate and start working in the industry.Author:
Dr. Gaurav Nagpal, Faculty of Decision Sciences, Business Analytics and Operations, BITS Pilani WILP
You're reading Twenty Commandments On Delivery Of Analytics Programs Or Courses In The Business
Praxis Business School launched its one year full time Business Program in 2011. The Praxis brand was new to this domain. When I heard about people mentioning Praxis on our blog initially, I thought it was one of the many programs which were started by Management Schools in the country. I dismissed it without opening their course page.
A few months after this incident, a couple of our community members had great things to say about the program. I usually consider this as one of the strongest early indicator about the quality of program and long term success. So, this time I talked to these community members for a long time over phone and also spent time understanding about their offering. I also went through the course details and looked at the profile of faculty.
There were quite a few things this program was doing differently:
They had taken a call that to do justice to the subject matter, they would run the program as a full time program over 12 months (as opposed to other part time programs).
The faculty was impressive with people from premier education institutes and industry experience.
Praxis was also providing campus placements – internships followed by final placements, for the students attending the program.
All of this was being offered at a price point comparable to part time programs in the country. The only concern I could think was that the program was based only in Kolkata. While Kolkata has been a city of scholars, I personally thought a program like this would benefit a lot if there was a larger industry ecosystem in the city.
Irrespective, I reached out to Praxis and asked them to visit the campus and interact with the students in the program. They happily obliged! We reviewed the program and included it in our rankings after that. Over one of the discussions with the team at Praxis, I mentioned that while Praxis was not suffering because of its Kolkata location, a program like this should also have a center in Bangalore.
A few years later (i.e. last week), I got a call from the Praxis team informing me that they are now launching the same program in Bangalore. I congratulated the team and had a long discussion with Prof. Charanpreet Singh about the vision and addition of Bangalore as a program location. Here are a few excerpts from the discussion:KJ: How do you look at the 5 years of journey of teaching analytics in India?
It has been a wonderful ride. We started the one-year full-time program in 2011 on the basis of suggestions made by our industry associates. As we did our own research, three things became abundantly clear:
There would be a massive global demand for data scientists moving forward;
There were no courses in the country addressing this need from a training perspective;
Analytics and data science were complex fields that would require a deep dive facilitated by faculty of exceptional quality.
We started with a batch of just 8 students in 2011 – and today we are an established brand in analytics in the country with perhaps the only 360 degree solution for the student – concept strengthening, experiential learning with labs and projects, and placement into the corporate world of analytics.
Our alumni have performed with distinction and we get repeat recruiters at our campus – two pieces of unambiguous evidence that our efforts are bearing fruit. And yes, in these five years the world of analytics has evolved with speed – and so has our curriculum!KJ: Take us through the thought behind the Bangalore launch.
As the awareness of analytics and data science gains momentum, the demand for good quality programs is bound to accelerate. Since we have chosen the high touch, in-class, full-time option, one way for us to grow and meet this increasing demand is to make the same program available in more geographies.
We started in Kolkata and focussed on getting our course content, faculty team and industry engagement right. We are now confident of a phased expansion, and Bangalore is quite obviously the best candidate for the first phase. It is the analytics capital of the country – with the highest number of people working with Tech companies and the largest number of potential recruiters.
As someone warned us a few months back – if you are in analytics you just have to be in Bangalore. We are excited about engaging with students in Bangalore and believe that this move will help enhance the Praxis position of being a top analytics institution.KJ: The three critical strengths of the Praxis program have been its curriculum, the faculty and the placement program. Do you see a risk of dilution in these attributes with the Bangalore launch?
We gave a lot of serious thought to this and came to the conclusion that this ‘extension’ will actually enhance our strengths. We are preserving the core of the curriculum – the subjects will remain the same across Kolkata and Bangalore, but each faculty member will, of course, add his/ her own flavour.
We have engaged with some very accomplished people in Bangalore with a mix of academic and industry experience to deliver the course.
This will strengthen our faculty team and create a rich resource-pool that we can draw on for research as well as teaching. Finally, a larger group of trained candidates amplifies our value proposition to the recruiters, as the demand for data scientists keeps galloping.KJ: Is there any change in the kind of applicants you are targeting in the two geographies? Can you briefly explain the selection criteria?
The selection process and criteria remain same irrespective of the geography.
We have two simple criteria for establishing suitability for this program – the extent of commitment to the domain of analytics, and the degree of problem solving passion and ability. Our program in Kolkata has had the full spectrum of students – from freshly graduated engineers and eco/ stats majors to professionals with 10 years of experience in IT and ITES.
The median would be someone with about 3-4 years of experience who is seeking a transition to a career in analytics. We have discovered that there are ready recruiters for the right talent and skill-set at every level.KJ: Who should apply to the Praxis programs – and why?
Let me sketch a picture of a Praxis aspirant – serious about a career in Analytics – willing to deep-dive and devote a year to learning – loves numbers and loves solving problems – is not daunted by technology or complexity.
If one is seeking a comprehensive, rigorous and cutting-edge curriculum supported by a strong placement program that creates compelling career opportunities, Praxis is a great option. I would also recommend that aspirants research the quality of the programs they are applying to, and engage with the institute alumni before they decide.KJ: There are several players in the hybrid and on-line space – which gives a much wider reach. You continue to stick to the full-time, high-touch program. Any specific reason?
Agree –on-line does give you reach. However, I look at two distinct types of audiences – one, those who are looking at analytics as an add-on to their existing set of skills with an objective of strengthening their capability in their current assignments; and two, those who are looking to transition from their existing careers into analytics.
Our programs address the specific requirements of the latter – analytics is a complex domain and a budding data scientist needs to devote his/ her full energy and time to the understanding of concepts and their applications.
Moving forward, we do have plans to address the needs of the on-line audience as well.KJ: Praxis is one of the few programs, which takes ownership of the placements of the students. What is the thought process behind it and how has this changed over years?
We are clear that our target students are seeking a transition into a career in analytics – that’s the reason they join our program. So it’s our responsibility to make sure of both – that they get the required learning that prepares them for this career and that they get institutional support in their quest for the all-important (and most tricky) first job in this area.
And I guess the two go hand-in-hand – as we understand the corporate expectations better with every interaction, we make appropriate improvements in our academic content and delivery.
Thus, by taking up the responsibility of placements with a lot of seriousness, we ensure that the quality of the program is continually enhanced. It also ensures that we keep adding new recruiters every year, in addition to retaining the present ones.
This approach introduces a lot of clarity in our selection process as well – if we feel certain candidates will encounter seemingly insurmountable barriers in entering this domain for any reason we make that abundantly clear to them and generally do not admit them into the program (unless they insist – and a few actually do – that they are happy to just learn and work something out for themselves).
From an outcome perspective, our curriculum has evolved substantially in the last 5 years and continues to be acknowledged as the most comprehensive and current program; and we have found the ‘first analytics job’ for over 90% of our students – consistently, batch after batch.
KJ: Thanks Prof. Singh for your time. As usual, I enjoyed talking to you. I wish you all the success for this program and hope that you continue to build the momentum and brand Praxis in future.To know more about the program, you can visit here. You can test your skills and knowledge. Check out Live Competitions and compete with best Data Scientists from all over the world.
More and more businesses are embracing the concept of big data versus treating it like just another buzz-phrase.
Once heralded as “the next big thing,” adoption of big data analytics is at an all-time high with no signs of slowing down anytime soon. With big data and business analytics software projected to reach nearly $200 billion in revenue by 2023, it’s clear that the business world’s decision to bet on data has paid off so far.
So, what’s the catalyst for such rapid adoption in the first place?
After all, not all data is created equal and the need for massive numbers varies from company to company. According to a 2023 big data survey conducted by NewVantage, the top reasons for big data initiatives include decreasing expenses, exploring innovation opportunities and launching new products and services:
Although big data has uncovered new opportunities for businesses to reel in revenue, it’s also created a slew of challenges for marketers.
According to analytics firm SAS, the most common problems presented by big data to marketers are three-fold:
Determining which pieces of data to gather: with so many moving pieces of any business, it’s natural for marketers to find themselves in a situation where they’re drowning in a sea of numbers
Picking between analytics tools and platforms: more data means more tools, which means more picking and choosing on behalf of marketers already saddled with time and budget constraints
Turning data into action: while it’s easier than ever to acquire mounds of data at a moment’s notice, the act of spinning that data into gold is easier said than done
Does that mean that all hope is lost for marketers looking to benefit from big data?
After all, data-driven marketing has become the norm of today’s businesses. Rather than trust assumptions or gut feelings, modern marketers are making decisions by the numbers available to them. In fact, spending on data-driven marketing was up over 60% between 2023 and 2023.1. Better Analytics = Better Design
As noted in the NewVantage survey, some of the greatest value of big data comes in the form of decreased expenses and faster launch of new products and services. This is being played out in the design world, where data is helping machines learn how to create sophisticated branding elements.
Your logo is the anchor of your brand, but getting one created can be a costly and lengthy affair:
Do it yourself, and you risk missing key elements that designers have been trained to understand.
Online platforms like Tailor Brands are eliminating the need for expensive designers and creative teams, getting brands up and running quickly and inexpensively. They’ve discovered how to take a user’s subjective input about their brand, and apply that to the huge amounts of data collected through their user base to provide machine-generate designs in minutes.
The system makes artistic decisions around colors, typefaces and layout based on design best practices and user feedback, essentially providing access to a massive database of design knowledge. Because their system is set up to continuously learn from all user input, they are able to spot design trends and preferences too, continually improving results.
All of this means brands no longer face the expense of working with logo design teams and can get out there and start marketing in record time.2. Perfectly Timed Content
Speaking of time, marketers today face some major pain points in regard to content. That is, squeezing the most out of each and every piece we publish is much easier said than done.
Fortunately, analytics can play a major role when it comes to timing and content distribution.
Consider how Growbots’ email marketing platform optimizes send times based on engagement and the peak activity of email subscribers based on data from over one million cold campaigns.
The results of their analysis are nothing to scoff at, either. According to Growbots, email delivery optimization has the potential to nearly double the conversion rate of any given campaign.
Collecting data on followers and subscribers ultimately teaches marketers the best window to reach them, time after time.
This same logic can be applied to the world of social media, too. That’s why solutions such as social scheduling tool Sprout Social created its “ViralPost” platform which automatically schedules tweets and posts in conjunction with the online activity of relevant influencers. This sort of scheduling clues us into both the power of data and automation for today’s marketers.
Big data often reminds us of a rather obvious detail of any given marketing strategy: we can’t be everywhere at once. With these tools on deck, however, the task of marketing around the clock actually becomes a reality.3. Boosting Sales
Given the cost and legwork involved with leveraging big data, there should be a financial incentive for hopping on the bandwagon, right?
Luckily, there is.
Take the world of ecommerce, for example, where a keen attention to analytics could potentially make or break a business. As noted by Dataconomy, big data has huge implications for sales as it applies to…
Optimized pricing: by tracking purchases and trends in real-time, brands can ultimately identify patterns that result in higher profits (something that 30% of businesses fail to do year after year)
Demand: big data analytics can forecast needs for inventory and essentially prevent the need for a business to ever be out of stock
Predicting trends: keeping a close eye on industry data provides opportunities to determine which products are buzzing with consumers and what’s falling flat.
For marketers making digital sales, even the most minor details uncovered via analytics could result in major profits or losses. Again, the information gleaned by big data often represents points that many marketers wouldn’t think twice about until they were aware of where they might be going wrong.4. Conversion Optimization
Yet the degree to which big data analytics can help accomplish these goals may be less obvious.
Bear in mind that 48% of big data is attributed to customer analytics, meaning that drilling deep to understand customer behavior should be a matter of “when” not “if”.
The rise of big data is a stern reminder for marketers to take a data-driven approach to conversion optimization. With variables such as headline and CTA copy to color scheme and imagery, there’s plenty to consider on any page of your site or store.
The more data you have to assess the behavior of your traffic, the better.5. Promoting Personalization
With so much emphasis on metrics in regard to big data, it’s easy to forget the people and relationships behind those same numbers.
The concept of big data creating more personalized experiences may seem like an oxymoron but just take for example how chatbots are being used to boost customer satisfaction.
For example, the more a fashion chatbot for a brand like H&M “talks” to a customer, the more it learns about their preference in terms of products. The bot is then able to come up with personalized product recommendations as a result:
While marketers aren’t expected to rely on robots, they are expected to regularly gather data from customers in pursuit of a more personalized experience.
Even beyond the world of bots, Amazon’s recommendation engine is a prime example of personalized recommendations via data collection. Considering that lack of personalization annoys nearly three-quarters of all consumers, the key is for marketers to deliver relevant recommendations only.
And although personalization is considered a must-do, 39% of marketers note that a “lack of data” is their biggest challenge toward making it happen.
Therefore marketers looking to get closer to their customers should learn more about them sooner rather than later. Through the power of big data analytics, that crucial personal connection is more than possible.Breaking Down the Benefits of Big Data
Big data analytics is about to become a massive part of enterprise of operations in 2023
In the era of data and information,Big data analytics powering digital transformation
Digital transformation is a global phenomenon that is driving a technological revolution all over the world. The transformation will continue to grow as IaaS providers scamper to cover the ground and build data centers. Digital transformation goes hand in hand withTransformation from SaaS to iPaaS
SaaS has been around for quite some time and has helped businesses optimize their businesses on the cloud. Earlier, the integration of SaaS has made headlines since it was relatively a new concept. But in 2023, we might not be able to see any revolutionary contributions from it. This is where iPaaS comes to play. As businesses try to avoidBig data will help climate change research
Solid data and proof might put the raging climate change research to rest by backing up the views and predictions by the climate change organization. The data might reveal some interesting insights about what is going on. The presence of legitimate data exempted from human biases will productively benefit the climate change debate.Big data might be used in local stores
Almost 90% of the local businesses and enterprises are using data to generate productive insights from these tools. The use of data-as-a-service is becoming more commonplace and is predicted to grow by US$10.7 billion by 2023. Customers might encounter DaaS in the form of purchased music, videos, and image files from multiple sources online.The use of small data is on the rise
Large enterprises can save massive amounts of time by just evaluating the most vitalData fabric will be the foundation
As data becomes increasingly complex and digital business accelerates, data fabric will become the architecture that will support composable data and analytics in its various forms. Data fabric reduces the time for integration by 30%, and for development by 70% since the technology designs will draw on the ability to reuse and combine different data integration styles.Composable data and analytics
The goal of composable data and analytics is to use components from multiple data, analytics, and AI solutions for a flexible, user-defined, and usable experience that will enable leaders to connect data insights to business outcomes. Composing new applications from the packaged business capabilities of each promotes productivity and agility.Big data to search novel medical cures
It is a primary responsibility for businesses to invest in human welfare. So, the use of raging big data applications in innovating cures for novel diseases might increase. Many scientists hope that by consolidating all the medical records accumulated on the planet, the discovery of medical cures will become faster and sooner than ever imagined.The use of XOps
The goal of XOps is to achieve efficiencies and economies of large scales using the best practices of DevOps for efficiency, reliability, and reusability while reducing the duplication of technology and processes and enabling automation.Planning and forecasting
In the era of data and information, big data is no longer new to businesses and society. It is a known fact that via big data solutions, organizations can generate insights and make well-informed decisions, discover new market trends, and improve productivity. As the amounts of data continue to grow, organizations are looking for new innovative ways to optimize big data. One of the major relationships of big data analytics with businesses is that their dependence on the internet increases, along with the amount of data generated by the rapid development and evolvement of technology. In 2023, the global big data market powered by big data analytics trends attained US$208 billion. It is expected that the big data market is expected to reach US$250 billion by 2026, with a CAGR of 10%. In this article, we have listed some big data analytics hidden trends to get to the core of its evolution in 2023.Digital transformation is a global phenomenon that is driving a technological revolution all over the world. The transformation will continue to grow as IaaS providers scamper to cover the ground and build data centers. Digital transformation goes hand in hand with big data , AI, machine learning, and the Internet of Things (IoT). Machine learning and AI tools will continue to handle the data generated from the data analytics to operate systems, make sense of complex hidden relationships, and store and project insights beyond human chúng tôi has been around for quite some time and has helped businesses optimize their businesses on the cloud. Earlier, the integration of SaaS has made headlines since it was relatively a new concept. But in 2023, we might not be able to see any revolutionary contributions from it. This is where iPaaS comes to play. As businesses try to avoid data losses and disjointed information between departments and platforms, iPaaS may provide logical solutions and become the next best trend in 2023.Solid data and proof might put the raging climate change research to rest by backing up the views and predictions by the climate change organization. The data might reveal some interesting insights about what is going on. The presence of legitimate data exempted from human biases will productively benefit the climate change debate.Almost 90% of the local businesses and enterprises are using data to generate productive insights from these tools. The use of data-as-a-service is becoming more commonplace and is predicted to grow by US$10.7 billion by 2023. Customers might encounter DaaS in the form of purchased music, videos, and image files from multiple sources online.Large enterprises can save massive amounts of time by just evaluating the most vital data instead of entire lots of the generated data. This can be efficiently achieved if businesses shift from big data to small data. It can enable more streamlined, fast, and bandwidth-sparring innovations to take chúng tôi data becomes increasingly complex and digital business accelerates, data fabric will become the architecture that will support composable data and analytics in its various forms. Data fabric reduces the time for integration by 30%, and for development by 70% since the technology designs will draw on the ability to reuse and combine different data integration chúng tôi goal of composable data and analytics is to use components from multiple data, analytics, and AI solutions for a flexible, user-defined, and usable experience that will enable leaders to connect data insights to business outcomes. Composing new applications from the packaged business capabilities of each promotes productivity and chúng tôi is a primary responsibility for businesses to invest in human welfare. So, the use of raging big data applications in innovating cures for novel diseases might increase. Many scientists hope that by consolidating all the medical records accumulated on the planet, the discovery of medical cures will become faster and sooner than ever chúng tôi goal of XOps is to achieve efficiencies and economies of large scales using the best practices of DevOps for efficiency, reliability, and reusability while reducing the duplication of technology and processes and enabling chúng tôi increased use of predictive analytics has also boosted the availability of affordable applications in the market, for both BI platforms, like Qlik or Anaplan and standalone cloud services like Amazon Forest, which can help the users to easily integrate predictive analytics in the systems. These tools can be used for planning based on the generated forecast data to make intelligent and profitable decisions.
blog / Sales and Marketing How Online Marketing Courses Can Help Entrepreneurs Stay Ahead of the Game
Marketing is a golden ticket that helps entrepreneurs scale their businesses to new heights and pave the path to success. The marketing industry is rapidly evolving from bot-assisted customer relations to augmented reality for product visualization. So, how can a business owner keep up with these constant changes? The answer lies in taking accredited online marketing courses to learn about this dynamic field while keeping up with a busy schedule. Here is a valuable guide to help professionals, entrepreneurs, and marketing aspirants make an informed choice and pick a marketing course that best suits their needs.How to Select the Best Online Marketing Course as an Entrepreneur?
The marketing industry is evolving so rapidly that the techniques and practices popular today can become outdated overnight. Enrolling in online marketing courses can help one stay ahead of the curve by learning about the latest trends in the industry. Given the variety of learning options available, however, it can be challenging to find the right course. Well, let’s make the search easier!
We have put together four key components to look for while picking online marketing courses:1. Check the Accreditation
Explore courses that are offered by reputed institutions or education platforms. This will ensure that the teaching methodology and academic curriculum meet industry standards and are up to the mark.2. Evaluate the Curriculum
Ensure that the course structure covers the fundamental concepts of marketing. In addition, make sure that the delivery method aligns with your learning preferences. This will help to understand core concepts better and build a solid foundation.3. Learn About the Faculty Members
Check the credentials of faculty members and industry experts delivering the course. Experienced professionals are more likely to offer valuable insights into the field.4. Read Testimonials and Reviews
Read about others’ experiences and what they have to say about the effectiveness and relevance of the course. Also, try to find reviews by other entrepreneurs to get a realistic idea about the course.
ALSO READ: Master Marketing for Business: 5 Key Elements for SuccessHow do Online Marketing Courses Benefit Entrepreneurs? 1. Cost-Effectiveness
An online course is likely to cost less than a fraction of a degree in marketing. It is a great way to acquire valuable marketing skills without straining the budget.2. Networking Opportunities
Enrolling in online marketing courses presents the opportunity to connect with other like-minded business owners and industry experts. In addition, one also gets to network with fellow entrepreneurs or potential collaborators, opening up a whole world of possibilities.3. Flexibility of Learning
Online learning enables self-paced learning. Besides, it allows one to choose from full-time, part-time, or offline formats based on individual schedules and requirements.4. Return on Investment (ROI)
ROI is an opportunity to upskill and apply these new learnings to target business growth. Moreover, it can yield significant returns for teaching professionals to optimize their marketing efforts. This could further result in higher conversion rates and boost revenue growth.What are the Online Marketing Strategies Every Entrepreneur Should Know?
Why would any entrepreneur want to miss out on the valuable benefits of marketing and its immense potential? Marketing practices should be a part of every business strategy, irrespective of the industry. However, it is key to identify which type of strategy will drive one’s company to success and work best in the long run. Let’s look at four essential marketing strategies that entrepreneurs should not miss out on:1. Search Engine Optimization (SEO)
Implementing effective SEO practices can help a business’s website rank higher on search engines. As a result, audiences can find its products and services more easily. A key strategy must be leveraged to boost traffic and engagement.2. Email Marketing
Setting up a solid email marketing strategy offers great potential to boost ROI. This is because it costs almost nothing to execute! Newsletters, churn mails, and sales engagement emails are a few types of emails to share with the target audience. Email strategy can also be automated, making it a more viable option.3. Social Media Marketing (SMM)
Social media platforms offer immense potential for building and nurturing an online audience. Besides, engaging digital content can increase brand visibility, inbound traffic, and a positive brand reputation.4. Conversion Rate Optimization (CRO)
ALSO READ: A Comprehensive Guide to Content Marketing in 2023 and BeyondDo Online Marketing Courses Really Impact Business Success?
Comprehensive online marketing courses can give entrepreneurs the skills to boost engagement and drive their businesses to success. Moreover, they provide a great opportunity to supplement learning with practical implementation. To begin with, they can apply their learnings by experimenting with marketing strategies and measuring results. Subsequently, they can refine their approach and make data-driven adjustments based on derived insights. This will help them reach a relevant audience, boost brand awareness, and achieve business success in today’s competitive environment.Get the Skills With Emeritus
The potential of marketing is truly endless when it comes to business. Whether improving sales or enhancing brand loyalty, effective marketing practices can help you achieve it all. If you want to upskill or acquire the latest marketing skills, check out these marketing courses by Emeritus. Learn from the industry’s best and unlock marketing’s power to future-proof businesses.
By Neha Menon
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If your computer takes forever to boot, even if you’re using a solid-state drive, its possible you have too many programs fighting over your computer’s resources. On the other hand, if everything is running smoothly and you’d like to add a program or app to your boot up, below you’ll find a few ways in which you can modify the startup process and programs.Setting Programs to launch on Windows Startup.
To get the ball rolling, we will demonstrate how to add programs and files to the Windows startup list, this is done by simply adding items to the Windows Startup Folder. Whatever you place in the Windows startup folder will launch when your windows system starts. (after login) You can add VPN programs, your favourite web browser, or simply open a word document. As simple as it all sounds, the startup folder is a little hard to find, the best and quickest method is to use the Run tool. To find the Run tool, press the Windows Key + R, then type: shell:startup into the text box and press Enter.
Note: This works with all types of files, folders, scripts or program .exe’s and will only affect the current user. If you wish to make the change across all users, you will have to run the command: shell:common startup instead, then place the files within.
Using the System Registry Tool to Change Startup Programs.
As above, open the Run tool using the Windows key +R key combo, type: regedit into the text box, then press Enter. This will bring up the registry editor, now in the registry window, navigate to the following location:HKEY_CURRENT_USERSoftwareMicrosoftWindowsCurrentVersionRun
The string value should look similar to this:"C:Program Files (x86)Mozilla FirefoxFirefox.exe"
Note: To disable any of these startup programs, you can use the below method for short-term requests. Or for a permanent solution, backtrack and delete all the keys and values you added. Remembering not to mess around with anything you didn’t create.How to Disable Programs that Auto Start on Windows Using the Windows Startup Manager.
The next set of instructions will show you how to remove startup programs and is much more useful than adding programs, as no one likes having to wait for Windows to boot. Depending on what version of Windows you are using there are two different ways to find the Startup Manager. If you are using windows 8.1 or older, you can find it by entering: msconfig into the Run tool, this will open the System Configuration window.
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