Digitization is driving the business world today. As IoT and Mobile First technologies are gaining momentum, businesses are getting influenced to enter the world of mobility. Mobile and web applications are becoming primary for personal, professional and commercial communication.

Mobility has opened a world of endless opportunities. However, delivering quality applications is an absolute must. This has increased the importance of a robust test data management system in across industries.

In this uber-competitive and complex digital world, test data management is not an easy job. Digital enterprises are faced with these key challenges in testing their applications and software products.

Shortage of data for testing
Testing with real-time data is dangerous, and certainly against data privacy regulations. To execute successful testing, enterprises have to create or identify relevant test data. Businesses are faced with a shortage of realistic information that can be safely used for testing purposes. A good way to fix this issue is to use a reliable automated software for test data generation that helps you create fictitious test data credentials effectively.

Vulnerability of test data
Most testing projects fail because of poor data quality. Data breaches, even the unintentional ones could be costly. A failure to protect test data from malicious activities could put a financial dent on your enterprise and cause serious legal implications. A range of data masking and de-identification solutions have now evolved to help QA professionals create safe test environments and stick to compliance regulations.

Safe storage of test data
Engineers spend a lot of time and effort in developing test data and selecting the right tools to execute the testing. However, storage of test data is often an overlooked aspect. Storing test data safely is important for reusability and audit purposes. The question is where to store test data once it’s generated. Selecting the right storage method for test data is crucial to effective test data management. Text files, spreadsheets, RDBMS and several TDM tools are the most common data stores to choose from.

Inaccuracy in performance
The success of an application depends on a lot of external factors, like internet connectivity, geographical locations, the device used, etc. Covering all these aspects of application testing is a challenge for most enterprises. To ensure that your apps perform well everywhere and at all times, you must scale up your QA efforts and deploy solutions that offer real-time testing.

In a world where there’s an app for everything, it’s really important to make sure your software products work well and stand out. The first step to successful performance of your products depends on the quality of your testing. Amidst several test data management challenges, the right solutions and the right approach to testing will help you launch quality products in the market.

As the world goes digital, security threats and cybercrimes evolve more rapidly. Take a look at these cybersecurity trends to keep it safe in 2018.

Over the years, cybercrime has grown at such an alarming rate that CIOs and business owners are constantly concerned about data security and unpleasant breaches in their organizations.

2017 saw some shocking leaks and some of the biggest data breaches of the decade including giants like Verizon and Equifax being affected. This rising tide of cybercrime has put an increased pressure on businesses to rethink about their cybersecurity systems.

So, what’s going to unfold in 2018? We’ve compiled a list of the top 6 cybersecurity trends to watch out for this year.

Preparing for GDPR compliance
The European Union’s General Data Protection Regulation (GDPR) is all set to affect thousands of enterprises worldwide from May, 2018. The GDPR is EU’s massive move towards securing European citizens’ sensitive data, regardless of physical location barriers. The law is applicable to all enterprises which use information related to EU citizens. Therefore, companies all over are preparing for the biggest data privacy regulation of the decade with vigor.

Internet of Things (IoT) and the risks involved
The IoT culture is on a massive high. Gradually, it has started to creep up in all aspects of our existence and it’s not late until the world will be obsessed with IoT devices. However, as much as we love the concept of IoT, it brings with it some cybersecurity challenges that cannot be overlooked. And with time, enterprises are taking measures to secure data within IoT devices and minimize enterprise risk.

Security with Artificial Intelligence (AI) and Machine Learning
Stringent regulations and increased risks of data breaches are making it essential to monitor IT activities and keep a track of data security. Mere dependence on security staff and traditional software is not enough. Companies are waking up to the need of the hour and adopting AI and Machine Learning to be able to detect malicious activities immediately and take safety measures effectively.

Preventing Ransomware Attacks
Ransomware attacks have been causing distress in digital enterprises for a long time now. In 2016, 18 million new types of malware were identified, and the numbers have been increasing ever since. The ripples of malware like SimpleLocker and WannaCry have startled companies globally and forced them to be more proactive in identifying and fighting ransomware attacks.

A rise in insider breaches
Digital enterprises are always faced with the threat of insider breaches. An insider breach occurs when a company’s sensitive data is exposed to malicious software due to phishing, theft or even carelessness of its employees. Studies reveal that 74% companies find themselves vulnerable to insider breaches. Organizations across industries like healthcare and finance report that almost 60% of their cyber attacks are carried out by insiders. And companies will continue to face insider threats in 2018 if they fail to address suspicious behavior well in time.

Use of Analytics in Cybersecurity
Companies have started using advanced analytics to help them deal with cybersecurity threats. They’re approaching methods like micro trend analysis, malware research and analysis and malware performance detections to identify any sources of threats and fight back immediately. And in 2018, more companies are expected to adopt analytics for better cybersecurity.

The estimated costs of cybercrime by 2021 are about $6 trillion and records show that 99% computers are vulnerable to security attacks. And with digitization, there comes a growing need to prevent data breaches strongly and combat cybercrime effectively. Strict vigilance and the ability to act fast in case of breaches is what will keep you safe from security incidents and heavy penalties in the long run.

Like the two sides of a coin, big data comes with its pros and cons too. Are you prepared to fight the five biggest risks of big data?

Over the years, big data has been the hottest topic in the tech world. The evolution of big data has taken the world by storm; and with each passing day, it just gets even bigger. Today big data touches every business, big or small, at some level. However, there are still enterprises that choose to ignore big data while they can clearly see the flood coming at them.

More data has been created in the past two years, than in the entire history of human existence. And, by 2020, about 1.7 megabytes of information will be created every second for every human being alive. If that doesn’t concern you as an entrepreneur, what else would? Fighting the big data flood is no joke, because it brings with it some serious risks to conquer.

Here are the five biggest risks that big data presents for digital enterprises.

Unorganized data
Big data is highly versatile. It comes from number of sources and in number of forms. There’s structured data, there’s unstructured data. There’s data coming from online and offline sources. And all this data keeps piling up each day, each minute. It’s overwhelming for enterprises to tackle such unorganized and siloed data sets effectively. A well planned governance strategy can bring you out of your dark data and help you make sense of it.

Data storage and retention
This is one of the most obvious risks associated with big data. When data gets accumulated at such a rapid pace and in such huge volumes, the first concern is its storage. Traditional data storage methods and technology are just not enough to store big data and retain it well. Enterprises today need a shift to cloud based data storage solutions to store, archive and access big data effectively.

Cost management
The process of storing, archiving, analyzing, reporting and managing big data involves costs. Many small and medium enterprises think that big data is only for big businesses, and they cannot afford it. However, with careful budgeting and planning of resources, big data costs can be mitigated well. Once the initial set up, migration and overhauling costs are taken care of, big data acts as an incredible revenue generator for digital enterprises.

Incompetent analytics
Without proper analytics, big data is just a pile of trash lying unnecessarily in your organization. Analytics is what makes data meaningful, giving management valuable insights to make business decisions and plan strategies for growth. With data growing at such an alarming rate, there’s obviously a lack of skilled professionals and technology to analyze big data efficiently. It exposes enterprises to the risk of misinterpretation of data, and wrong decision making. Hiring the right talent and applying the right tools is crucial to make relevant decisions from a big data project.

Data privacy
With big data, comes the biggest risk of data privacy. Enterprises worldwide make use of sensitive data, personal customer information and strategic documents. When there’s so much confidential data lying around, the last thing you want is a data breach at your enterprise. A security incident can not only affect critical data and bring down your reputation; it also leads to legal actions and heavy penalties. Taking measures for data privacy is not just a good initiative anymore, it’s a compliance necessity.

Big data is an extremely overwhelming concept for most enterprises. It’s huge; it’s complex and carries a set of challenges and risks. However, a solid plan, a clear roadmap and the right technology will help you fight the risks of big data successfully.

Big Data is making big noise in the digital world. How long till it affects you?

The Information Technology is a dynamic space that keeps evolving with time. In the recent past, there’s been big buzz about big data. But has it affected you already? Or are you still thinking it’s not for enterprises like yours? All businesses, regardless of their size or nature produce data; and hence sooner or later, big data is certainly coming for you.

As the name suggests, big data is huge, massive sets of data too large to be managed by traditional data management tools and software. It is characterized by the four V’s that build its foundation– volume, velocity, variety and veracity.

Volume– Mammoth sizes of data is accumulating within data driven enterprises. On an average, about 2.3 trillion gigabytes of data is produced every single day.

Velocity– The rapid speed with which this data generates and piles up is alarming.

Variety– This big data comes from disparate online and offline sources and in different forms, mainly structured and unstructured.

Veracity– The generated big data is highly abnormal and inconsistent, making it difficult for enterprises to make sense of it and build trust in their data.

And, because of these factors, enterprises across the globe are getting serious about it and taking measures to make the most of big data. If left unmanaged, big data can turn out to be a huge challenge. However, if harnessed and utilized well, it can introduce new opportunities for businesses.

Why is Big Data such a big deal?

The amount of structured and unstructured data is expected to grow manifolds, almost by 60-80% every year. Undoubtedly, Big Data is here to stay. Whether or not you realize it today, it’s not far until big data hits your industry. And when it does, you don’t want to fall behind.

And hence, it is important that businesses, big or small, prepare themselves for a data explosion and adopt technologies that can help them make sense of their data, make appropriate use of it and turn big data to their advantage.

Industries impacted by Big Data:

Big data is everywhere. It is influencing diverse businesses in multiple ways. Here we’re discussing some of the major industry niches have been deeply impacted by the emergence of big data and analytics.

Finance and Insurance
The finance and insurance industry is largely dependent on data coming from various sources. Big data technology brings an array of opportunities for financial enterprises to explore. This includes innovative payment mechanisms, faster data processing, real time analysis of customer and financial information, intelligent market forecasts and protection from fraudulent activities.

Healthcare and life sciences
We have entered the age of Medical Internet of Things (MIoT). There have been massive advancements in the healthcare industry since the emergence of big data. From maintaining patient details, to medicine records, quick diagnostics to digital monitoring, personalized treatments and production of evidence based medicines big data is tremendously changing the way healthcare and life sciences industry operates.

Retail
Retail is another data intensive industry, both in terms of online and offline data accumulating every day in huge numbers. The retail industry has seen a sea change with Big data and advanced analytics. It helps retailers to introduce more effective payment gateways, manage inventories efficiently, analyze market trends, and optimize product pricing to stand out from competitors.

Telecom
The telecom industry deals with plenty of data on a daily basis and big data has opened up significant growth opportunities for telecom businesses. Telecommunication enterprises are exploiting big data and business intelligence to understand customer behavior patterns, enhance user engagement, reduce customer churn, and improve data processing abilities.

Marketing
Modern marketers are making use of big data to the fullest. They have chunks of raw data coming from the internet, right from website clicks, to user details, geographies and search histories, and what not. Big data enables marketers use this information to drive their marketing efforts in the right direction like creating a workable sales funnel, running personalized marketing campaigns, predicting market trends, generating leads and maintaining existing customers effectively.

All in all, Big Data is reshaping the information technology world, and opening doors to greater avenues. The rapid rise in the volume of data, and privacy threats could certainly be a daunting aspect of big data. But with the right data management tools and effective big data solutions, you can make big data your biggest strength and grow your business exponentially.