Growing Prevalence of Start-ups in Data as Services
Data as services is an SEO and data science services company that uses AI driven internal linking and neural SEO networks to increase prevalence and visibility of its clients on various search engines. It has been growing rapidly and has acquired more than 20 global clients every month even during COVID-19 because of its neural SEO network value. Being a player in a game that does not have many major players, it has allowed and made Data as Services serve its clients, many of them being start-ups, adequately and suitably and also have proven to be reliable for them. Data as services, as a company for its clients, is crucial because it helps them in boosting their product promotion and increases their visibility and prominence on search engines. It serves as an advertising tool for products desired by the customers looking for them. The customers, by default, look for the products they are looking for on search engines and it is important for the start-ups and corporations to make sure that the products they are looking for are visibly accessible to them. Data as Services functions and acts as a medium between this relationship of these corporations and start-ups with their customers by making it visible and accessible for the customers, their required and desired products that the clients are providing. It serves the clients by contributing to the promotion of their products and serves the target customers by presenting these products to them on the search engines. Data as Services is growing and will keep growing because the search engines like Google also keep growing to serve as a bridge between corporations and customers and it is as important as ever for the corporations to introduce and present their products to their customers.
Data as Services operates through a neural network. Neural network is widely regarded and considered to be the future of Search-Engine-Optimisation (SEO). Neural networks are a string of algorithms that recognize the underlying relationships and equations between a set of data by replicating, emulating and mimicking human behaviour or the way a human brain works. This model based on AI is central to machine learning which Google uses to better and improve the experience of its users. Neural networks influence other processes too. From market analysis to chatbots to product recommendations to customer service, the application of neural networks is what causes and impacts them. Machine learning enables us to go to the depths and nuances of the content in a website. This is why it is able to come up with a new SEO formula and rank the web pages better. AI has had the biggest impact on website content with more emphasis on quality rather than keyword filling. Earlier, users had to fill their searches with keywords that were related to the content they were looking for. Now, AI has made it based more on quality, purpose and relevance. Neural networks are able to determine the quality of blog posts and articles and cut down the range of options and data to provide the user with the most preferable and suitable results. They also make content-driven searching more favourable for users. As AI replicates the way a human brain works, neural networks complement the users to get the required search results not on the basis of matching keywords but rather, on the basis of actual meaning and the content that the user is specifically looking for. This helps in results being accurate and precise as per the user’s needs. Neural networks improve the efficiency of search-engine algorithms. Search engines like Google do a great job of utilising the users’ search history and records to improve the overall experience in the long run. From locations to searches to frequency of websites visited, algorithms analyze all these details and information to make it more user-friendly. It also helps in web-page testing which further helps in comparing and paralleling the contents of websites to show or display the results with options either higher or lower depending on the user. Testing of website pages is important for recognizing the upsides and downsides and advantages and disadvantages. Digital advertising has also enjoyed a major boon because of AI and the application of neural networks. Placement of products at ideal times, rectification and showing of the right results irrespective of obvious spelling errors and the suggestion of ads based on the target users are all done through neural networks. Neural networks meddled with AI has undoubtedly contributed to the enhanced user experience.
Data as Services uses neural networks for increasing product value, relevance and visibility that its clients have to offer. The average needs of the customer keep growing and so do the corporations and start-ups to match and keep up with the growing customer demands. In this day with age of technology being a major driving force behind selling for corporate houses as well as start-ups and technology also making buying much more comfortable, easier and convenient for customers, Data as Services offers just the right ploy and also the ideal mix to balance both the sellers’ interests as well as the buyers’ interests. Data as Services is that established middle ground between the sellers and the buyers which upholds the best interests of both the former and the latter, and that is of marketing and purchasing. It’s a relentless and a vicious cycle of customers’ needs increasing every day with the start-ups catering to these needs which further only makes the customers’ needs grow every day. This has made a company like Data as Services vital for both the parties to help in important aspects like advertising, promotion, increase in product value and relevance, providing the customer with preferable and favourable results, etc. Data as Services has been acquiring clients rapidly with more than twenty clients even during the time of a global pandemic and has, in a space of just two months, acquired more than fifty clients globally. This is because; the field that it’s operating in is ever-changing and a developing one with its demand increasing day after day after day. This demand comes from both the sellers and the buyers. Online shopping and e-commerce are a major part of the national and international market and economy today. While a search engine may not be involved in these spheres directly, the very process of a user going to the internet to look for something sets off with a search engine and this is when the importance of an SEO and data science services company like Data as Services comes into play.
It’s ironic to note that a company like Data as Services that works to increase relevance of search results for its clients as well as the users is increasing its own relevance in the corporate and the occupational world. The trajectory with which it operates is always growing, which means that its demand will always grow too. This has made Data as Services an emerging player in a field which is still young and hence, gives it a major opening to operate and function in. There’s a lot of potential to look forward to. What makes it so endearing is the fact that it can manage to serve as a bridge to bridge the gap between the buyer and the seller and also provide services that ease their interactions with each other. Using AI, ML and neural networks, it becomes a part of a larger system that is changing and growing every day and has several layers that broadens to global communication and international as well as national markets and economies. This is the reason why start-ups globally are turning to Data as Services to benefit from the vast applications of AI and ML. While it knowingly and voluntarily caters to the start-ups and corporations, it also benefits the users and customers online. Search engines will always remain the preliminary foundational step to a bigger process of ‘looking up the internet’, and hence, SEO will always be instrumental for the results favouring and catering to the users’ requirements. This also means that the responsibilities, obligations and duties of companies like Data as Services will always remain intact yet continuous in nature. The world of start-ups, businesses and the overall corporate culture will also continue to remain prevalent. This further means that, the height and extent to which these corporations and start-ups would go to serve their customers will always keep on increasing which in turn, would keep the customers’ expectations always high. AI is also in the weak and the general AI stage and hasn’t reached the strong AI stage along with ML developing every day. The textbook of technology and its limits are always expanding day by day and the big corporations are turning to these advancements to sell their products and increase their value to meet the market demands. This cyclic process which is extensive and yet pertinent to the current scenario is the reason why a company like Data as Services which serves both sides of the spectrum will keep growing and emerging as a major player in the game.
Demerits of Data as a Service (daas) ?
While DAAS is reaching new milestones every passing year, it still has some shortcomings which need to be coped up i.e., challenges to encounter are as follows:
Data Security: Since DAAS is all about cloud networking sharing, all the data, resources and services are present on cloud meanwhile on the web, which is an intermediate place between user and provider. Hence, the high risk of data stealing.
Restricted Abilities: There may arise circumstances wherein the number of tools available for working with data is limited and hence forcing the user to work upon with the tools available on their DAAS platform. Variation in tools may take place from what provider supplied to what end-user possesses on his platform.
Delay in Transfer: It may take a good amount of time to transfer bulky volumes of data from one end to other. This usually, happens because of the restrictions created by the bandwidth. Thus, eliminates frequent data transfer possibility. There may be problems relating to insufficiency of the source to provide up with data and resources in the specified format.