Super Fast Processing

Not a long time back, telecom billing was all about charging and rating basic services like SMS and calls. However, with the evolution of technology, we are seeing a rise of new technologies that are pushing the traditional telecom billing systems to the limit. Companies simply cannot rely on what has worked in the past. It is time to innovate and be prepared for newer tech like IoT and 5G. The best way to undertake a task as challenging as telecom billing is by employing cutting-edge telecom billing systems that are based in the cloud.
Cloud-Based Telecom Billing Systems: What to Look For?
Not all cloud-based telecom billing systems are equal. You need to be very thorough and settle on the best billing system to ensure success in your telecom billing and monetization of services. Below are some important features, which you should look for in your next cloud-based telecom billing system.
Ability to work well with present and future services
As the pace of technology evolution increases, it is very much likely that telcos would have to launch newer services at a faster rate. And, emerging technologies like 5G and IoT are much more complex than the technologies launched in the past. Therefore, it is best to partner with a vendor that can offer telecom billing systems that can not only meet the requirements of the present but also the future. Also, the telecom billing solution should be completely scalable vertically to meet the rising demands of new subscribers.
Security of data
An online billing system based in the cloud is always exposed to hackers’ threat. To ensure security of subscriber data that is stored on the cloud, it is essential to enforce sturdy encryption measures. Also, these encryption measures need to be updated from time-to-time, in order to stay ahead of hackers that are always on the prowl. A single hacking incident can undo the hard work done over many years, which is why; security is extremely crucial in any online telecom billing system.
Backed by APIs for different business use cases
A telecom billing system may serve you well, but it may not be able to meet every new requirement. Let’s say, you don’t have a pre-existing partnership with a shipping vendor but you need one to ship your IoT SIMs. In this case, you may choose to customize the software but it is a costly investment. A better way to deal with such situations is to partner with a telecom services provider that can issue an API that immediately lets you partner with a shipping vendor and also lets you manage the partnership and all the related transactions. As APIs help address particular requirements without taking drastic steps like buying a new software solution, they are far more economically viable in such scenarios.
Convergent billing
Customers of today seek complete transparency in billing. This can only be done if you employ cloud-based solutions that come with a centralized charging system like an OCS. An OCS charges all the services – both event-based and session-based – at the same place. This allows the charges of all the services to be printed on a single invoice, which customers of today actually want.

Staying one step ahead of the game at all times is the key to success in modern-day business environment. As data generation via online platforms reaches an all-time high, the need to put it to good use is growing. Massive data processing solutions have become the need of the hour and the need for data stream processing is at an all-time high.

What is Data Stream Processing?

Data stream processing is a technology specially devised for addressing the requirements of Big Data tech. It is utilized to query constantly generating data streams. The biggest difference it has with other data processing technologies is that it processes data within a very short time limit after the data is received by the system.

As hackers discover new ways to intrude into systems and get their hands on vital customer information, companies are looking to neutralize the emerging threat. One way to curb these apparent dangers is to analyze security logs that are generated during everyday operations.

The Importance of Security Log Processing

Every event that takes place in an organization leads to the generation of information in the form of logs. In the first stage, all the logs that are created are aggregated. Primarily, there are four ways to aggregate logs – syslog server, event streaming, log collection via software agents and direct access of networking devices.

Real-time data analytics is a prevalent term in the industry, but most people don’t understand its true meaning. If you think real-time is always instantaneous i.e. an input through a user instantly leads to the generation of an insight, then you can’t be more wrong. Different applications have different timeframes, in which, an insight can be useful. Therefore, help in bulk data processing needs to be sought according to the exact requirements of a business.

Varying Examples of Real-Time Data Processing

Telematics are often used in self-driving cars for navigational purposes. The feedback received from the road needs to be updated to the server in a fraction of a second, in order to derive an insight that can maneuver the car in the right direction. Any delay can cause a catastrophe. On the other hand, in an industrial storage solution where the temperature has to be decreased/increased depending on the conditions of the stored items, the time window for making the change is relatively larger. The insights derived for both these cases would be deemed real-time, in spite of the large difference in time between the two incidents.

As the dependency on data increases, companies are looking for new avenues to process and analyze data for business purposes. The vast troves of data stored in a myriad of databases offer a wealth of opportunities, but only for those that are ready with tools for processing large amounts of data. Superfast and real-time processing of millions and millions of transactions is the key to unlocking business opportunities presented to an organization. However, one thing that needs to be kept in mind before employing a superfast platform is to analyze its ability to handle load, especially during peaks and surges of data influx.

Database processing is a key area of interest for companies looking to maximize data value in today’s context. Everything revolves around data nowadays and it can provide significant advantage when you are competing in choked markets. To maximize the potential of data for your business, real-time data stream processing is needed. And, for effective next-gen real-time insight derivation from large databases, you need an in memory database processing program.

The Importance of In Memory Database Processing

In the past, processing was done solely on the data stored in the hard disk. Although this type of processing was accurate and efficient in terms of cost, it wasn’t the best in terms of speed.

MemSQL is an in-memory SQL DBMS (Database Management System) that help in bulk data processing and allows companies to generate relevant insights for the welfare of their business. It can be exceptionally useful in financial and telecom business domains where there is a lot of data generated in real-time.

MemSQL for Real-Time Data Processing

MemSQL allows for constant observation and unearthing of relevant insights for business. Along with that, it comes with fully-scalable reporting functionality and analytics that are disseminated across the various data entry points. Some of the major advantages of utilizing MemSQL are listed below:

As dependence on data grows, business world is waking up to a new reality. Entrepreneurs have realized the potential of data and have started capturing all the data streaming in and out of their systems. But as vast troves of data accumulate, the importance of big data processing technologies is rising.

The Significance of Big Data Analytics

Big data analytics has become vital for companies because of its immense potential to provide insights. These insights lead to quicker and faster decision making, which helps a company exploit market trends at the right time. The importance of timing can be elucidated with the following example:

As companies look to leverage AI technologies for deriving insights that are useful for their business, we are seeing a rise in the requirement of solutions for processing millions of transactions per second. Especially when it comes to real-time data processing and analytics, the demand is even higher.

Advantages of Real-Time Data Processing

Real-time data processing has many advantages for a business, which is why; it is frequently utilized by companies for business gains. Some of its major benefits are listed below:

Data value is dependent on many factors such as data relevance, data volume and the amount of time spent in deriving value from data. However, due to a rise in competition and shorter window of opportunities, businesses are looking for data that can be put to good use in real-time. Nowadays, the window of opportunities to exploit insights has become very short. This has happened because competitors are often using similar databases and coming to the same conclusion after analyzing it. Hence, to really make the most out of a database, it is imperative that you utilize it before anyone else does, which can be done with real time data stream processing. Also, there are many fields, in which, real-time data stream processing is extremely useful e.g. IoT. Therefore, real time data stream processing has become more of a necessity rather than luxury.

‘Find a Problem and Solve It’ – This is a well-known saying in the business world, generally recited by experienced entrepreneurs to educate young business men. People who swear by this mantra believe that any business can be successful if it is created with the intention of solving a problem. When it comes to telecom, this theory is best applied to MVNOs who are looking to break into a highly competitive telecom market. Complex telecom operations not only require you to search and find a meaningful problem to solve, but also deliver the solution in form of your own services and bill subscribers according to a preset tariff. The last part is where the real challenge lies.
While you can use your innovation to find a problem and solve it, billing has to be in your thoughts at all times. Error-prone billing has seen many amazing MVNO Solutions fall flat, not long after their launch. Hence, it is important to find a problem, its solution and also the best telecom billing systems that can ensure proper monetization of your services and accuracy at the same time.
How to Find the RIGHT Telecom Billing Services for Billing Success?
A billing solution that allows you complete flexibility in launching plans can be the difference between success and failure. As an MVNO, it makes good business sense to look for an MVNE that has a good track record. But even more important than the track record is your MVNE’s ability to fulfill the following critical requirements:
1. A billing system that can offer innovative discounts: As an MVNO makes profit by serving the interests of regional subscribers; it needs to show innovation in stacking up different services as part of a bundle. Even more important than assembling these services is its ability to offer discounts that entice subscribers. By offering creative discounts like cross-product discounts, a customer can popularize itself and solve the problem of customer churn.
2. Convergence in billing: Trust between operator and subscriber is extremely important in the telecom industry. Lack of trust directly relates to the problem of waning customer loyalty, which is at an all-time low due to an increase in competition. To solve this fast-spreading issue of fickle customer loyalty, complete transparency is required in the billing process. Complete convergence offered by a telecom billing solution can help you print all charges incurred by customer in a single invoice. This allows a customer to see all the services he is using and the charges applied. There is no room for ambiguity in this. And, as modern-day customers value transparency more than anything else, your MVNO benefits greatly with convergence in billing.
Security: For an MVNO that has a small subscriber base, security of customer information should be absolutely sacred. Any compromise or leak of customer account information can shut your business in a few days. This is why; you should keep account security as your top priority. Partnering with Telgoo5 immediately guarantees robust security for your network. It is a top-notch telecom billing services provider in North America with a consistent track-record of delivering on its promises and serving many reputed partners across the globe.

Gone are the days, when establishing a high-quality network infrastructure was the sole requirement of a successful telecom operation. Nowadays, the success of telcos is decided by their ability to launch innovative plans that evoke customer interest. Basic services like voice and SMS are no longer the difference makers. There is a need to bundle basic services in attractive packages and complement them with new and evolved services. If a telecom operator wants to succeed in the current state of the industry, it needs to have a quality telecommunications billing software solution to meet all the emerging requirements.
The Importance of APIs
Application Program Interface (API) has become extremely important for telcos. Due to frequently changing requirements in the industry, a telecom operator needs to find ways to adapt its services according to the market and preferences. However, the cost of sending the telecommunications billing software back to the vendor for customization or buying a new software solution is quite high. This is where APIs come into the picture.
Consider a case where you want to deliver SIM cards to your subscriber; however, you do not have any previous partnership with a shipping vendor. In this case, you can use an API that gives you direct accessibility to the shipping partners of your vendor. Likewise, if you need to integrate different payment gateways, you can simply install an API that instantly gives you access to different gateways for collecting payment.
These are just a few situations, in which, APIs can come in handy. When you use a quality telecom billing service like Telgoo5, you get access to many more APIs that can come in handy in different situations.
Other Things to Look Forward in your next Telecommunications Billing Software
Apart from powerful APIs, you should also look for the following attributes in your next telecom billing software:
Analytics for deriving insights about subscriber preferences and market trends
Telecommunications billing software solutions track and also generate copious amount of data. This data can be leveraged by using an AI-powered software solution that draws business critical insights from the dataset. These insights have many uses. You can learn a lot about customers’ purchase habits, preference for specific data plans, market turbulence etc. After understanding these business-critical insights, you can create effective business strategies.
Convergence in billing
OCS is an integral part of telecom billing system architecture. By procuring a 3GPP compliant OCS as part of your billing system, you can ensure complete convergence in billing and eliminate the risk of any revenue leakage. A quality OCS charges all the services based on number of events or length of sessions. The centralized charging allows you to create convergent bills with charges for all the services reflected in a single invoice.
Security
Customers’ vital data is stored in your telecom billing solutions. This data needs to be protected at all cost. Any lapse in security can result in customer fallout. Hence, you should take security very seriously and always partner with a telecom services vendor that not only uses strong encryption but also provides periodic security updates to counter future threats.

Big Data is a word that refers to collection or combination of large pools of data sets to discern patterns that vary in size, complexity and growth rate. The volume, velocity and variability of data makes it difficult to capture, process, manages or analyze by any random tools and technologies. It is significant for individual firms & government to gather large pools of data and analyze it to make better decisions, enhance productivity and grow business.
This complex data is driven by modern technologies weblogs, Internet searches, social networks such as Facebook, Twitter, LinkedIn etc., portable devices, smart phones, call center records etc. No technology has come up to define its growth as it is expected that the growth rate is likely to increase in future. To get better results and utilize data effectively, the big data must be combined with other enterprise applications such as Enterprise Resource Planning or Customer Relationship Management etc. Companies are able to get better understanding of their business, competitors, customers, services, products etc. when the big data is captured, mined, processed and analyzed effectively. The effective data leads to enhanced productivity, business improvement, better customer experience, increased sales, lower costs and defined product and services.
The following are some widely cited examples that focus on the relevance of big data:

Healthcare companies use it effectively and creatively to drive quality With the help of smartphones and other devices, it offers business opportunities to target customers in close proximity to a store such as coffee shop or restaurant and increase revenue and a chance to target new customers too The use of social media and web logs from ecommerce sites of retailers help to understand customer's requirement and enable effective micro customer segmentation It is important to get the relevant IT data from different sources in a good volume to improve Information technology (IT) troubleshooting, security breach, prevent detection, and increase speed Industries such as banking, finance, insurance and shopping invest in big data process to detect fraud and help to prevent such industries that processes online financial transactions for corrective action.

Big Data Key Challenges:

A lot of industries find it a daunting task to determine the best use of the data that is available through this process Due to new, complex and emerging technologies, organization needs to be updated about these ever changing new technologies. It will be vital for such companies to balance the business needs associated with its cost Privacy, security, and regulatory considerations need to be maintained at any point of time so that confidential customer and business data are not disclosed to any unauthorized party Since big data is Voluminous and varied in content & structure, it might lose its value over time, therefore, it is necessary to utilize new tools & technologies and eliminate big data effectively if not required so it does not affect your current business processes
With the worldwide expertise and service providers of big data, you can now get the consistent and comprehensive implementation on any scale. Keep reading and learn more us.

A big data processing business may seem like a real leap for someone considering an Internet startup, but it's not as far out of reach as you might think. In fact, "big data", commonly defined as data sets so large they can't be handled by most average software tools, is becoming a necessity for so many applications these days and it requires trained professionals to deal with this type of specialized programming. Think of it this way... with more and more people using technology every day, the traffic on the information superhighway has become quite congested. You've got smart phones, tablets and notebooks allowing people to access information no matter where they are, any time of the day or night. All of which adds up to major convenience... but it also leads to the inevitable traffic jams.
Then you have applications that make use of larger, more complicated sets of data in order to provide their services. They're like the big rigs on the road pulling trailers with signs reading "wide load". They need more room than usual to make even the simplest of turns. You can't put just anyone behind the wheel of one of those vehicles; it takes someone with particular skills to operate them properly. The same holds true on the information superhighway. There are thousands upon thousands of small, average users maneuvering their way through traffic with no problems, but when you throw a big user into the mix, things can get dicey. Unless there is someone at the controls who knows what they're doing and can manipulate that wide load you could be looking at major cyber "accidents".
Now you can see where a big data processing business can be so valuable. If this kind of complex data is not handled properly it can cause major issues for the entire system and most companies can't handle that kind of work on their own. This creates a built-in market for someone who can step in and provide the kind of big data management that these businesses need.
And just like those big rig drivers, you can't trust this kind of work to just anyone. Businesses need someone they can trust to understand the complicated nature of big data and what it takes to manipulate it. By marketing yourself as capable of handling this kind of data process, you will be setting yourself up for success by opening all sorts of job opportunities. Because big data is a big deal these days, it is used in a wide variety of applications by everyone from the government to the manufacturing industry. Companies like eBay, Amazon and Facebook all use big data for tracking customers and processing orders; banks use it to keep track of your credit score; scientists apply it in research. Simply put, big data is critical to almost every aspect of our lives.
If you're considering establishing a presence online, a big data processing business may be the way to go. It's a service that can prove valuable to any number of companies and one that won't be dying off any time soon. The information superhighway is a reality now, and professionals who can keep the big blocks of data running on it smoothly can help to make it work for everyone.

You may have heard the term big data before. It is usually measured by petabytes. To give you an idea how large this actually is, you can forget about megabytes or even terabytes. 1000 gigabytes equals a terabyte. A thousand of these and you've got a petabyte. This is an astronomical amount of data and it is because the infrastructure of the company has allowed it to get this large. Whether it's a website, a data processing center or something else, there is too much data. It is almost impossible to collect all the data when it is so enlarged. Most companies can barely store it let alone utilize it effectively. As a result, there needs to be some sort of fix for it.
There are many companies that help with this big data. Whether it's storing it or leveraging it, you get access to the data again. This can mean getting your data on demand. You get a workflow that can actually be utilized because the data is condensed. Resources are limited when there is so much data. It slows computers down and IT data centers become overcrowded because there is so much required storage. In addition, a lot of the time the data is simply not used. This is because the same data is on multiple computers, causing overlap and ineffective use of the current storage.
Instead of having a company help with the current data and improve the workflow, you can also turn to the clouds. Cloud computing is one of the newest forms of technology that is being utilized instead of a bunch of servers. Rather than sharing all of the data on a server, it is stored online in what is referred to as a cloud. The benefits to this are a huge cost savings as well as physical storage requirements. When data is stored online, this eliminates huge data centers, a ton of electricity, and potentially entire IT departments. All of the big data is simply outsourced to a cloud.
Big data is just too massive to process on its own. Search engines encountered this years ago because of the datasets required for people to search on. Now, however, there is better technology including distributed analysis and better processing capabilities. Large scale jobs can be distributed and coordinated using cloud architecture. The same data can be run on multiple machines without a physical machine in the building. The cloud is an online format so that as long as there is access to the internet, there is access to the data.
Rather than spending money on huge machines and processing solutions that changes the entire infrastructure of an organization, companies have recognized cloud computing as a very innovative solution for big data. It features the ability to pay as one goes on a monthly or annual basis instead of tying money up in capital assets. The regular cost simply gets written off as an expense of doing business. Cloud technologies help in many assets of big data. These include the ability to search for millions of records, log analysis, generation of reports as well as index creation process. Data just gets larger and larger, eating up resources and it isn't something that's likely to just go away.
Big data is only going to continue getting bigger. Adding more servers isn't the answer - it's only going to increase a company's expenses. There are many cloud providers on the internet, featuring the ability to transfer and process data much more effectively - and eliminate a lot of expenses as well.

Big Data has become a new buzz word in the IT industry. Everyone is talking about it and repeatedly using it to impress others, even if they themselves don't really know what it means. It is often used out of context and more as a marketing gimmick. This article aims to explain what Big Data really is and how it will be useful in solving problems.

Physics and Mathematics calculations can give us the exact distance from the East Coast of the USA to the West Coast, accurate to about 1 yard. This is a phenomenal achievement and has been applied to various technologies in our daily life. But the challenge comes in when you have data which is not static, which is constantly changing and changing at a rate and in volumes which are humongous to determine in real time. The only way we can process this data is by using computers.

IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. But there are many more aspects of it. Big data can be described by the following characteristics:

Volume is the size of the data which determines the value and potential of the data under consideration and whether it can actually be considered as Big Data or not. Variety means that the category to which the data belongs to is also a very essential fact that needs to be known by the data analysts. This helps the people, who are closely analyzing the data and are associated with it, to effectively use the data to their advantage and thus upholding the importance of the data. Velocity refers to how fast the data is generated and processed to be useful. Variability of the data can also be a problem for the analysts. Veracity is the quality of the data being captured. Accurate analysis depends on the veracity of the source data.

Analogies

An article on the Tibco Blog provided a very simple analogy to understanding what Big Data really is. Their blog says that:

"One analogy for Big Data analysis is to compare your data to a large lake... Trying to get an accurate size of this lake down to the last gallon or ounce is virtually impossible... Now let's assume that you have built a big water counting machine... You feed all of the water in the lake through your big water counting machine, and it tells you the number of ounces of water in the lake... for that point in time."

A better, more visual analogy is presented by Paul Lewis of Hitachi Data Systems. He often explains about Big Data by showing a picture cartoon filled with hundreds of people who are doing different things in the picture, looking busy. He explains:

"You need to find the person with the suitcase of money (Value)... but there are many people (Volume), all walking at various speeds running to work (Velocity), from all walks of life (Variety), some are crooks (Veracity)."

Importance and Benefits

One of the major reasons why we need Big Data is for prediction and analysis. One of the best examples where Big Data can be seen in action is the Large Hadron Collider experiment, in which about 150 million sensor deliver data 40 million times per second. After filtering and refraining from recording more than 99.999% of these streams, there are 100 collisions of interest per second. Another important example is Facebook, which handles over 50 billion user photos.

Healthcare is another area where Big Data can play a significant role. One of the most amazing example is Google Flu Trends, which analyses search data from various locations and uses the Data Analysis to identify patterns of Influenza epidemics and endemics around the world. Although this data is not necessarily accurate or may have a lot of false positives, it highlights the potential of what such data can show you.