Alisha Sharma

Big Data Certification in Malaysia gives you the basic skills and experience required to analyze vast amounts of data that contribute to good decision-making. Given that just 0.5 percent of the publicly available data is being processed and used, there is a huge potential waiting to be taken. This course will direct you through your understanding of how to use the technological resources, data sets and application scripts involved with the big data analysis. Big Data Certification in Malaysia is suitable for someone with a technological mindset employed in every field. You will develop an understanding of the collection and interpretation of data as well as the practical application of Big Data knowledge across the course. Covers foundation topics in: Big Data, Data Science, Machine Learning and AI-based courses offer an insider's perspective into the complexities of how and when data is so important. Big Data Data Science Machine Learning Deep Learning Artificial Intelligence Exploring opportunities for AI in your organization Best practices for AI strategy For professionals in mid-career and senior roles: Big Data Certification Malaysia is targeted to practitioners in mid-career and senior positions who have no coding or development history. Built for non-programmers. Issues discussed by concrete examples. Introducing Python coding in both transparent and non-intimidating environments. Master algorithms for an approach to problem-solving. Introducing functional and relatable calculations and statistics. Learn to do what you're doing in Excel by Python coding. Good knowledge of network infrastructure and design. Emphasis on problem-solving and critical skills. Big Data Certification Malaysia gives you the basic skills and knowledge required to analyze massive quantities of data, identify trends and allow smart decision-making. The foundation course is non-technical and is open to executives, experts, and decision-makers. Participants can acquire realistic knowledge of data collection, data processing, data analysis, data simulation, and machine learning. The course covers industry, computer science, and mathematics and offers insights into active data science ventures. The course was planned from the ground up to appeal to those with no previous coding experience. Participants will be introduced to the Python programming environment by easy-to-understand experiments. Our teachers should meet with students one on one in the class to ensure that each participant learns the basics. Big Data is a method for providing information into decision-making. The method uses humans and technologies to easily analyze vast volumes of data of various types (traditional organized table data and unstructured data, such as images, video, email, transaction data, and social media interactions) from a number of sources to produce a pool of actionable information. Organizations continually need to evaluate facts in order to make decisions that increase performance, income, and profitability. As relational databases have increased in scale to accommodate these criteria, companies have also looked to alternative techniques for processing massive volumes of information. These emerging technologies are also referred to as Big Data. Gartner defined three main features for big data: Quantity, Size and Range. Big Data Certification Malaysia can be used to handle various types of formats outside conventional transactional structures. Meanings for Quantity, Velocity, and Variety differ, but most big data meanings include volumes of knowledge that are too difficult for conventional systems to handle — either the quantity is too high, the velocity is too small, or the variety is too large.

The idea of integrating and benefiting from artificial intelligence has invaded the minds of enterprise owners as well as venture capitalists like a swarm of bees. They can taste the honey but not without suffering the occasional sting. The word AI has gathered so many connotations and been explained in so many different ways that the perception of the non technical investors is completely clouded. Startups are trying to integrate artificial intelligence in their business processes but facing failure more often than not. We will try to look at the possible reasons behind this predicament. Lack of vision The capacity and the achievements of artificial intelligence is quite limited. The first and most important requirement is to understand how a certain enterprise can benefit from AI. Not only does this understanding involve consideration of the current technological scenario but also the foresight to imagine the usage of future technologies. The foresight is necessary in order to control the investment. This vision is often lacking in modern Indian startups. They desperately want to include AI in their company profile but often do not know how. Unrealistic expectations The lack of vision is accompanied by unrealistic ideas about the power of AI implanted by the marketers working in favour of the vendors. The vendors come with polished used cases and excellent presentations which may inspire the startup to invest in AI based technologies like, automated chatbots and marketing analytics models. While these devices can be exceptionally useful over an extended period of time provided the constant flow of quality data, startups often find it difficult to wait for the return of investment for such a long time. Budget constraints Technologies like artificial intelligence, machine learning or natural language processing do not come cheaply. Whether you want an inhouse team of operators or outsource the services to a vendor, you must be ready with large expendable funds. This is why the large conglomerates find it easier to deploy AI, they can easily assign large funds to the development of these sectors and wait for the ROI. But Startups can easily run dry with one bad investment. Scarcity of trained professionals The acute skill gap in the applied AI and machine learning sectors keeps the average salary for skilled personnel so high that it is often impossible for startups to cope. Moreover the quality of employees is not guaranteed by their certificates and hiring one wrong person can wreak havoc on a startup’s finances. This is why applied AI courses have become so important and relevant for both the employers and the job seekers. Applied AI is a new sector that desperately needs able minds in large numbers. These are opportune times for the students with a knack for numbers as well as for computer science to venture into the challenging yet exciting world of artificial intelligence. The possible way out Extensive planning and foresight can guide startups to successful integration of artificial intelligence. They must invest in the right services and keep patience till the return of investment. And all startups deploying AI should set a goal of employing inhouse data science and AI teams. There is no limit to the possibilities with proper planning and perseverance.

Data scientist might be the most celebrated job role in the world of technology right now, but it is definitely not the only one worth soughting. Data oriented environment is built through various steps through the cooperation of multiple people of various ranks. It is quite foolish to undermine any of these roles because all of them are important and any of them can be your stepping stone towards the desired goal of becoming a data scientist. Let us glance through some roles that need data analytics skills.Data architect and database architect A data scientist needs data. The data has to be kept somewhere. That somewhere needs certain features that make the best data easily available. The data reservoir needs to be maintained and protected. These reservoirs are called databases. The database architect is responsible for the building, maintenance and security of complex databases. It is one of the most important analytics jobs and yet strangely underappreciated. Technically, the role of data architect is slightly different. They monitor and control the flow of the data across the company. These two roles are often inseparable. The required skill sets are not too widely varied. You need a good base in mathematics and statistics, relational database management skills, data visualization skills, knowledge in SQL and NoSQL. Some programming skills in Python or R can also come handy. Data analyst This is actually an umbrella term which is used to refer to a lot of different job roles. Primarily the data analyst is responsible for mining the data followed by a visual representation. The data available to a company has to be made sense of. The data analyst sorts the data and tries to locate patterns in the data. This could produce some insight. The findings then have to be represented in a visual and comprehensive manner, so that it can make certain suggestions to the company. The tools involved in this job are Spark, SAS, R and lately some cloud computing skills. Business analyst This could ideally be a part of a discussion about business management unless data and business had been so deeply related. Business analysts try to be a bridge between the productive and the managing sections of a company. They try to look at historical data to figure out what has been happening. They are also responsible for guiding the business processes to the most beneficial future. Business analytics requires a firm knowledge of data analytics tools as well as a strong business acumen. Data scientist Arguably the best of the lot, a data scientist is ideally a visionary with incredible quantitative and computational skills who is supposed to replace intuitive decisions with scientific choices. The title scientist carries a lot of gravity. A data science course helps you get started; it teaches you to use the various tools and technologies to find patterns in data, turn those patterns in insights and then create models where the insights would predict the future. However, a data scientist is galvanized with years of experience and efforts. The sooner you get started the better.

If your business craves for more rewards and wants to excel in lead generation services, outsourcing your services can help. Lead generation is all about influencing potential partners that visit the business offerings to take its service. Lead generation process performs through various ways like hoardings, content marketing, social media, videos, marketing through website content, etc. Every company wants leads so that more and more people come to know of the business service and take its benefit to give more customers that are loyal. However, lead generation is not so easy and generating leads in-house may not be getting you the same results as expected from the business. In such cases, you might opt to outsource lead generation services to an external partner that has experience in generating leads from the best medium possible. The channels through which leads are generated are content, emails, ads, blogs, social media, referral marketing, etc . Lets’ talk about the benefits of outsourcing lead generation services: You invest time in those who are important Lead generation is all about finding prospects that are capable and ready to buy the business service. Outsourcing helps to attain positive leads who are actually looking for your business service. When you get external partners’ support, they know the exact platforms to highlight your business leads, they know the audiences’ preferences and have an effective strategy to grab the users’ attention. This is the reason expert partners’ will help your business invest time in those who are actually important. If you do not have a team skilled in generating leads, you may face false leads coming in that would be of no use later. Therefore, to avoid wasting time and energy, it is better to outsource to an experienced partner. Focus A huge team helps to transmit the business message to the audience. The team requires training so that the lead generation task is in place. This is where the need to outsource your B2B lead generation arises. As hiring and training are very costly and needs the involvement of a huge sales team, it is better to outsource, so that the in-house agents are free to focus on business intensive tasks. Strategy making is very essential to help your business grow in this competitive world. This is why outsourcing is helpful as it saves the business time to give on strategy making for overall development. Access to the right technology Businesses need the right technology, access to phones and computers to perform the task for lead generation services. Not all companies have the time and capital to invest in in-house lead generation, which is why they outsource processes. Getting an external partner for B2B lead generation, the business has access to the appropriate software, capable to find positive leads for the business. Moreover, correct software manages and collects feedback from the customers bringing enhanced satisfaction to the customers. Lowering operational expense Working with an outsourced company that specializes in sales and lead generation, your business saves operational cost. How? Outsourcing helps the business avoid the need to maintain in-house infrastructure. Getting an external partner, your business gets all the required amenities on time, which helps in reducing expenses. Evaluating results is better It is subsequent that when an external experienced partner looks after the business service, it is easy to evaluate results with their expertise. The partner knows the appropriate measures to boost business service and they link in new aspects to boost results. Specialized partners plan strategical enhancements for the business to bring more enriched results. This enhancement in planning is not possible with in-house agents as they have limited experience and are not well aware of the market trends. Focus on core competencies Lead generation services have to keep the potential competencies in mind anytime. If you are a company working on lead generation process, knowing the potential threats is essential. To combat the competitors, it is important to know their strength and weaknesses with the market needs to meet customers’ requirements before them. This process requires in-depth knowledge about the platforms to generate leads to get the most of the customers. Moreover, businesses need to know the challenges so that offering services accordingly ensures enhanced results. In such challenging situations, getting a partner who has good knowledge of the market and trends is helpful. Outsourcing saves time to focus on business improvements keeping the competitors in mind. Moreover, developing lead generation services in-house requires going on with all the processes from scratch and thus outsourcing is a good option, where experts look after the business service giving time to the business to focus on competencies.

Business failure is very much on the cards if you are not good at lead generation. It is because more leads you generate, more you can thrive in today’s hyper-competitive market. That’s could be the prime reason why securing a high rate of lead generation is the main goal of 66% of organizations. However, filling up the sales funnel with quality leads isn’t as easy as it was a few years ago. This is so because it is very hard to draw the attention of prospects towards products and services. Thus, most of the businesses avail services from lead generating companies to secure an incredible growth rate. Today, we are going to shed light on 3 tactics that can really help to load the sales funnel loaded with quality leads, so have a look: 1. Use powerful headlines to get results via content marketing Content marketing has always been one of the most effective lead generation tactics, and that’s the main reason why most of the lead generating companies use it to keep the sales pipeline filled. Generally, businesses handling the lead generation process don’t get the desired results after developing quality content. Can you guess the prime reason behind this? Still guessing? Let it be, as the answer is unconvincing headlines. Well, it is true that potential customers first search about products on the internet, but it doesn’t mean that they open every link present on the search results. Usually, those write-ups grab the attention of prospects that have powerful headlines. Therefore, if you are an owner of a company and trying to get desired lead-related results, come up with enticing titles. Here, we would like to reveal the fact that 73% of buying decisions are made because of well-written headlines. Plus, there is a notable drop in the bounce rate, which again improves the chances of generating leads. 2. Be mindful while sending lead generating emails Email marketing is one of the lead generation techniques, which is still doing wonders for marketers. The major reason behind this is most of the people nowadays have an email account for personal and professional work as well. So, email marketing seems like a perfect source to reach the targeted audience. However, companies sometimes make blunders while sending lead generating emails, which as a negative consequence, reduces the chances of generating the desired number of leads. Generally, email content quality gets compromised, thereby, lead generation rate drops significantly. Here are some tips to send effective lead generating emails. • First and foremost, create captivating subject lines. • Try to add top-notch quality in your email content. • Include business-related images, videos, etc. • Make sure the placement of CTA buttons is done to perfection. Have you tried everything, but still unable to fill up the sales funnel? Avail services from lead generating companies. 3. Never drop your guard during social media marketing After content and email marketing, social media marketing is the tactic which is being used by most of the lead generating companies, because it helps to reach the targeted audience quite easily. You shouldn’t be having any doubt because social networking platforms like Facebook, Twitter, etc. have a large user base, which points to the high availability of the targeted audience. However, some enterprises struggle to reap benefits via social media marketing, and the reason behind this is again carelessness. Usually, organisations handling the lead generation process make mistakes while sharing posts on public platforms, thus, they face hassle while generating the desired number of leads. Here are some suggestions that will explain how social media marketing should be done, so have a look: • Make certain your caption is attention-grabbing. • Add relevant and trending hashtags (3 to 4 are enough.). • Try to shorten your link (if any) as this would help SM users to share it in their contact zone. • Ensure all your image and video posts are in high-quality. Want to generate quality leads in a jiffy? You can opt for a paid Ads option or bag services of recognized lead generating companies. Thanks for reading!