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Chennai, India, – January 31, 2018 – Trove is an online search platform that helps find and use resources relating to Australia. It is collaboration between the National Library, Australia’s State and Territory libraries, and research institutions around Australia.

Trove’s origins can be traced back to a project launched by the National Library of Australia in August 2008 aimed to build a portal for all of the Library’s online discovery services. As a partner of National Library of Australia, Ninestars was instrumental in contributing more than 10 million pages of digitized Newspaper to Trove platform. Apart from English content, Ninestars also digitized the Australian Chinese Newspaper, a maiden attempt by NLA which was a huge success prompting NLA to go for more Chinese content digitization.

“It’s amazing the volume of work we have accomplished together, and it’s an absolute pleasure working with you,” stated Wan Wong, Director of National Library of Australia, ANDP project about Ninestars ’s contribution.

About Ninestars

Founded in 1999, Ninestars is an IP-driven Digital transformation industry leader. Ninestars helps Media, Publishing, Communication & PR, Government, BFSI and Publishing industries to redefine consumer experiences, strengthen their digital core, embrace digital transformation, and realize the full potential of their content. With over 18 years in the industry, Ninestars Information Technologies Pvt. Ltd. has been instrumental in revolutionizing the media industry with innovative projects in newspaper archive digitization and contributing to the digital transformation journey of more than 150 organizations worldwide. Ninestars partner with some of the most effective organizations in the world like ProQuest, IBM, Jastec, IISc, Abbyy, Hewlett Packard, Quark and Adobe InDesign to help achieve their shared values.

We are talking about the digital transformations to watch out for in 2018 and discussed 5 of them in the last blog. If you have not read the previous blog you can read it here…

Moving on, let’s look at some of the other important digital technologies, which will move towards the peak this year and make a mark on the business landscape.

Augmented reality

AR is a digital trend to definitely bet on. Googles AR core, Snapchat Lens Studio, and Apples AR kit are proving that investing in AR today will open up new revenue streams tomorrow. These platforms are also providing people an opportunity to create their own augmented reality applications. AR is easily accessible and can be exploited via smartphones, thus providing a ready market. Various analysts project that mobile based augmented reality will act pivotal in adoption and usage of augmented reality, providing sustainable revenues. From Headsets to now smart contact lenses, AR is not limited to just visualizing things but also provides flexibility of creating things that can be harnessed by dynamic programming.

As we are talking about AR we also need to throw a light on Mixed Reality, which is basically a combination of VR and AR. MR or Mixed Reality is still on early research phases but holds considerable promise in business landscape.

Low code platforms

The need of extensive resources required to build application quality user experience applications across mobile, web and desktop development is not feasible for every organizations. This is because UX services with intensive coding are expensive, especially for small and medium sized enterprises.

Low code platforms have tapped into this space and provided accessibility to creation of advanced multi format applications faster. Traditionally it takes at least six to nine months to develop a custom application or a mobile app, which can be substantially lessened by use of low code platforms and can be done by an internal team simultaneously with other tasks.

Considering the increasing volatility in markets and ever changing customer demand patterns, having a quicker and affordable option towards building successful and updated applications is the need of the hour. Major giants like Google coming up with low code platforms only stresses on the fact that this tech holds potential to turn big.

5th Generation Cell Processing

As discussed in our previous blog, IoT and emerging trends like AI require higher speed and seamless connectivity prompting the need for speedy development of 5G wireless standards. Looking at the current progress in research to introduce 5G we can see that it suffices all the 3 major needs, more number of connections, reduced latency (up to 40 times less than 4G) and increased throughput (transmission capacity to billions of bits)

Key players in the telecommunications industry like Verizon, AT&T, Samsung and Vodafone have already forecasted that 5G will be introduced soon and are gearing up to be equipped with compatible gadgets and infrastructure when 5G is commercially introduced. Although we can’t say for sure that 5G will be a thing of 2018, we can definitely say that it’s not too late before 5G will be the new essential.

Hybrid APIs

We think it’s safe to say that we are all in the API economy, and so choosing the right API connection for your organizations or project needs is important. As the API management platform market is maturing, enterprises are formulating holistic API strategies. All that said 2018 will be the year when people look at the APIs from the user perspective. 2017 was the year when we saw many large vendors acquire individual software vendors focused on API management for eg, Google’s acquisition of Apigee, pointing towards the need of hybrid cloud integration platforms. This can help organizations incorporate data and applications across varied and diverse cloud infrastructures.

This year organizations will be seen automating API frameworks which can be a systematic approach from creation to retirement of applications bringing the Life Cycle API management platforms into the limelight too. Moving away from the current approach we can expect organizations to use same tools and practices for managing their public and private APIs cohesively.

Apart from the above, the Open API initiative can also be seen gaining traction and opening up new business avenues.

CX-Optimization

Investing money in customer experience has been looked upon as a gamble since a long time as the returns might not happen right away. For the past decade we have been observing steady intervention of top-level management in creating value for the customers and raising the level of customer experience. Forrester reported this year that the top three challenges for a customer experience program include organizational culture (54%), organizational structures (45%), and processes (41%), which can only be solved with C level cognizance. The other important thing observed is that customers no longer want to watch long ads, disclaimer video, infomercials etc. instead want answers personalized to their background, and they want it quick. We can see machine learning stepping in here, as it can leverage the real time information it receives from the end user.

Customer experience is seen to get a data makeover, as the data generated is limitless and when leveraged efficiently can achieve higher levels of customer satisfaction and reduce the churn rate.

As Organizations are still battling to cope with the pace of changes that happened in 2017, it’s time to gear up for what 2018 has in store for all of us. Everyone had Artificial Intelligence and IoT on the tip of their tongues throughout 2017, while block-chain made its way towards the spotlight, its peer Bitcoin ate up all the attention. The year 2017 can be called as a learning curve for various companies. As many organizations were struggling and figuring out how to make the most of the new technologies flooding in, the likes of IBM, SAP, CISCO etc. were gearing to stay ahead in the race to exploit these opportunities in the business landscape.

Here are the 10 Digital Transformations trends, which were backstage in 2017 but are undoubtedly going to be hard to miss in 2018. In this two-part blog post, we will open the doors to the most important digital transformation trends that will most likely make waves in 2018.

Internet of Things

The last year was functional in shaping up the future of IoT in business and not limiting its use to creating just a network of things. With extensive data aggressive organizations working with IoT, we see 2018 a revolutionary year for IoT enabled businesses. Not only do we see IoT revolutionizing data collection and curation, but we can also expect it pushing different trends like analytics, Edge computing and 5G processing in the market.

There are currently about 8.4 billion connected devices in the world – somewhat short of the 26 billion that Gartner predicted in 2013 would be in use by the end of the decade. And there is only going to be an upward movement from here in terms of growth of smart devices. Apart from collection of data from this tremendous number of devices, the primary need is going to be in cutting through the clutter and finding those key business insights as businesses are going to need them in real time. This will forge the need for exponential speed and emergence of edge computing as the need of the hour. It will also push Mobile operators to direct their efforts towards faster implementation of 5G-cell processing.

Hybrid Analytics

In 2018, analytics is working closely with the digital innovation as the IoT, sensor, machine learning and AI, block chain and business data networks integrate to create whole new hoard of chances in the business world. This year looks as the changing point for the future of cloud analytics looking at the amount of cloud data that is being created. This is in turn pointing the need for organization to look at analytics from a hybrid perspective i.e. across various cloud platforms.

As natural language ushers in and provides users the flexibility to ask for specific answers from the data, obtaining insights from the information collected and processing it to understand business problems and formulating solutions is going to be relatively faster which in turn will open new avenues in augmenting the current state of use of analytics in sales, customer service and research. As machines learning, AI and big data walk hand in hand, insight trading will create new business ventures in curating data. This will turn make it easy for big organizations to gain access to rich insights from data that they do not own. Booming use of machine learning algorithms will change the face of sorting through large volumes of data to obtain relevant and contextual problem statements. In the era of customer being the king understanding your consumer precise needs will become much easier as analytics will take charge of obtaining the cream of customer intelligence.

Edge computing

For everyone working with intensive IoT technology and cloud computing, edge computing arrived as a blessing. With all the bandwidth, time and storage expense incurred to send data to centre storage data centers and conduct analysis, cloud seems to be taking a back seat in 2018 with edge computing emerging as the hero. Simple concept of installing micro data centers near the data sources enables the organization to conduct near real time data analysis, which is beneficial as, much of the data created nowadays is time bound. Gartner predicts by 2022, 75% of enterprise-generated data will be created and processed outside the data center or cloud, up from just 10% today.

For completely exploiting the benefits of edge computing we need to have substantial and sustainable IoT infrastructure ready as device connectivity is at its core. Taking science and technological advancements which have zero to none interference by humans for e.g. Self-driving cars are highly dependent on real time decision making and cannot depend on the latency caused due the large distance between the device and the cloud.

Edge computing not only saves costs by limiting the time taken to collect and analyze data but it also helps your organization stay connected with your data sources at all times and acts as a positive differentiator for your organization.

Blockchain

Once a complicated tech known only with respect to Bitcoin in the context, blockchain now as an individual technology is getting noticed by people. Blockchain is entering the mainstream world and gaining recognition as one of the most secure transactional technology we have in the world. As various crypto currencies can be seen making their way in the business landscape awareness about blockchain and its implementation in various other sectors apart from financial give and takes is coming into prominence.

The healthcare sector is next major user of blockchain, it uses blockchain to eliminate counterfeit pharmaceutical drugs. Nonetheless we can a large number of companies accepting crypto currencies and wallets as mode of payment for e.g., WordPress.

The basis of blockchain is disruption and thus it has the power to disrupt many deep-rooted industries especially the ones with lot of middlemen and intermediaries. Small players and startups engaging in creating business opportunities by the use of block chain is coming up as a trend this year with players like Excel Coin, Acorn Collective, Hybrid Block, ODEM etc. working to change the way a service can be delivered.

AI

Undoubtedly the most awaited trend of 2017, “Artificial Intelligence” became quite the buzzword by the end of 2017. We saw machine learning and AI being introduced as the one stop solution for all business problems but as we enter 2018 we are observing that even though AI holds tremendous opportunities it also comes with some set of limitations. Companies are trying to cut through the hype and are looking for specific and clear business applications for AI. And so we can say that 2018 is turning out the year where organizations want more than proof of concept.

Expert systems were crucial in lowering monotonous workloads especially in the financial world. Understanding the fact that integration of machine learning with the current use of expert systems will lead to more efficient usage can help organizations not only cut down on turn over time but cut costs and increase accuracy.

As AI techniques like deep learning come into the picture helping gain access to critical data insights, we can expect businesses not only wanting to know information but also understand the reasoning process putting emphasis on the back end. This will give impetus to improved Natural Language Generation systems.

Stay with us as we explore what more the digital world has in store for you as this year unfolds. Next article dives into predicting how 5G, Augmented reality, low code platforms, Apps and APIs and CX(Customer Experience) will emerge this year.

Keeping a finger on your customers’ pulse has always been the key in driving successful business enterprises. Understanding what users feel about your products and services, implementing the changes requested, solving the problems faced, coming up with new means to reach them better can be crucial while taking the next step to understand customer mindset

One of the best ways to gain considerable consumer insights is through sentiment analysis. Sentiment analysis has been around for a few years but because of the lack of real time data and deep learning tools, it stayed in the backseat. However, with abundant data availability and various deep-learning models at disposal, Sentiment analysis is again gaining momentum. So what exactly is sentiment analysis? What technological infrastructure is it backed by? And what can sentiment accuracy do for your business? Let’s explore answers to all these questions.

Sentiment Analysis?

Sentiments, alternatives for feelings, attitudes, opinions, advices etc. can be a handful to handle. Sentiments can be defined as various subjective impressions a person can have about what he or she is exposed to. So what has a business got to do with this? In business terms, we can relate this to comments, reviews, discussions, suggestions, or experiences your customers have when experiencing your products and services.

Sentiment analysis deals with analyzing all that the customers have been talking about your brand, be it positive or negative. Every word that a consumer puts out on any media platform can serve as a means to understand the feelings of the user. Often used together, words like semantic orientation and polarity, sentiment analysis entails identifying and characterizing user content by means of natural language processing, advanced machine learning methods and statistical tools. It is otherwise referred to as opinion mining too.

Which Questions Can Sentiment Analysis Answer?

From finding whether a product review is positive/negative to grasping the acceptance of your new marketing campaign, sentiment analysis can give you all the answers hidden in a simple text. It broadly comprises of,

Information extraction: This enables discarding the relative information and mining the right content for you.
Flame detection: Analyzing the nature of negative content being put out regarding your brand or any specific offering you have in the market.
Polarity Detection: Enables you to associate specific keyword with the reviews and comments generated and identify polarity if any exists.
Classifying: This guides in sorting out the good and bad content and studying the nature of words used in it, usually speedup by counting the number of positive and negative adjectives used.

Conducting continuous and productive sentimental analysis can throw a light on what your customers like and do not like, their preferences, specific things they would like to change, their experience with the service delivered and if they will recommend your services and products to anyone and or buy again from you et al. Creating a data set from these answers and running continuous analysis enables good feed to business intelligence.

Techniques Used

Although there are various tools and software which are readily available to conduct sentiment analysis but accuracy is the key. A weak sentimental analysis can not only give insufficient clarity but also misguide the conclusions derived due to inability to understand the polarity well. Sentimental Analysis is a text classification, which largely works on a machine learning mechanism with specific algorithms.

Supervised: When this technique is used, the machine already has a certain classified data set with which it takes reference of, to classify text mainly into positive, negative and neutral polarity. Popular models here include the maximum entropy model classifier and support vector machines.

Unsupervised: Here as there is no prior data set for reference the working popularly used is part of speech tagging. Once the words are extracted, semantic orientation is estimated, cumulative semantic orientation of the collected phrases helps in classifying.

Challenges

Sentiments are generally expressed as opinions and are subjective to the user and not facts. It is fairly obvious that machine-learning systems used cannot exactly interpret what a human being wants to express. As the way people express feelings in words can be tricky calling for the need for a strong sentiment analysis model. Let’s look at the challenges experienced while conducting sentiment analysis,

Taking literal meaning of content can lead to problems, as opinion texts are complex to interpret. They can comprise positive and negative things together and one positive thing does not indicate a positive classification thus, only lexical analysis can be misleading.
Humor and Sarcasm is extremely difficult for a machine to understand unless it has been trained under tremendous data sets of such data and has undergone many simulations. But now as deep learning is evolving this problem has become relatively easier to tackle.
Predispositions on the side of a business enterprise can lead to analyzing only that data, which can feed to the hypotheses, they have in their mind. On the other hand keeping an open mind enables you to see the problems from a more holistic view and understand that things may not be the way you had predicted. This in turn opens up new findings from the data to improve on.
How Important Is Sentiment Accuracy?

Sentiment accuracy refers to how accurately can you interpret the feelings of your user base or analyze the conversations you are a part of, on the web. Sentiment accuracy is the core of any sentiment analysis, as without higher rates of accuracy conducting sentiment analysis seems useless. There are various techniques by which you can work hard on increasing the accuracy of your analysis and they largely depend on obtaining the right data. Right data can only be facilitated by the use of right information extraction tools, cleaning and classifying this data will be the next step. Using good semantic orientation tools, which can score individual phrases and words, does not guarantee accuracy. The other way by which you can increase accuracy is exposing your ML model to extensive training by feeding it with large variety of data.

Finding the right tool or opting to conduct it in-house is a decision which is crucial as, you may find the right tool or not and doing it in-house may be costly for some and not for some. At the end of the day the deciding factor should be the accuracy obtained by the models and a fair call based on accurate results. Higher levels of accuracy will add value to your strategic decisions and help in creating value for your consumers further.

For a complimentary, no-obligation discussion around ideas on how to measure customer sentiment for your enterprise and your industry sector, please get in touch with us now.

Bangalore, June 6, 2018 – Building on the brand’s DNA of innovation and furthering its commitment to be the leading end-to-end provider of Digitization, Ninestars has announced a partnership with Piql, a high-performance unique storage solution provider.

Ninestars, a global leader in Digitization and Media monitoring services, today announced a new partnership with digital and physical storage solution provider Piql that will provide secure availability of digital content. Integrating Piql’s digital and physical storage solutions within its suite of Digitization and Digital services for the newspaper and publishing industry, Ninestars will be able to offer end-to-end digitization and storage solutions for its customers to help them become truly digital institutions.

Co-founder and Managing Director of Ninestars, Gokul Krishnan said, “Our first priority are our customers, and we are always looking for ways to improve our customer services. This partnership with Piql, will help us extend our reach and allow us to provide advanced end-to-end Digitization capabilities for our customers.” The companies will collaborate to deliver unique Digitization and storage solution reducing intricacy, optimizing operational agility, and improving security.

Piql, the leading provider of data archiving solutions, offers organizations with the most reliable, secure archive on an eternal data carrier (piqlFilm). “We are excited to offer our products to publishers and Newspapers, and thrilled to be partnered with Ninestars. By keeping data offline on a future-proof storage medium, we aim to preserve the cultural heritage of the world.” said Rune Bjerkestrand, Managing Director of Piql.

This flagship offline-online solution allows for 500+ years of complete security, reduced storage cost, guaranteed authenticity and future accessibility. Piql also offers storage in the Arctic World Archive—a safe and secure location to preserve digital memory, in a world where few places are safe from natural and man-made disasters.

This natural partnership will benefit clients of both companies, expanding the services available to offer a complete preservation solution for the publishing and newspaper industry.

About Piql

Headquartered in Drammen (Norway), Piql offers Digital Storage, Vault Storage, Restoration, and other related services through an extensive network of trusted partners.With an ambition to reshape digital preservation with a holistic approach, Piql’s solutions are designed for maintaining the integrity of customers’ data whilst ensuring they can be reproduced at some point in the future.

 

About Ninestars

Founded in 1999, Ninestars is an IP-driven Digital transformation industry leader. Ninestars helps Media, Publishing, Communication & PR, Government, BFSI and other allied industries to redefine consumer experiences, strengthen their digital core, embrace digital transformation, and realize the full potential of their content.

Leveraging its two decades of expertise & technology, Ninestars has been able to take leadership positions in Digitization, Media Intelligence, and Digital space. With a top-notch R&D division, Ninestars has brought about path-breaking solutions resulting in filing of six patents.

Bangalore, Feb 18, 2019 – Ninestars, a global leader in digital content transformation solutions, today announced that it has attained the PRIVACY+ certification by Professional Records & Information Services Management (PRISM) International. Ninestars is the first Indian company to be accredited with the PRIVACY+ certificate and only the second in Asia. The certification further demonstrates Ninestars’ commitment to security and privacy of customer data, a critical requirement more now than ever.

Owned and administered by PRISM International, PRIVACY+ is an international certification program allowing participants to demonstrate their commitment to ensuring the privacy of customer data. Only 34 organizations worldwide have achieved this certification.

Regarding the achievement of PRIVACY+ Certification and becoming the first Indian company to do so, the managing director of Ninestars, Gokul Krishnan said, “Protecting the data of our partners is our top priority and achieving this certificate solidifies our commitment of protecting the physical storage and handling of hard-copy records of our clients. With this certificate, we want our stakeholders around the world to both understand and embrace, our commitment to security.”

“Commenting on the achievement for the company’s press release, PRISM International CEO Bob Johnson said, “By achieving PRIVACY+ Certification, Ninestars has demonstrated extraordinary operational excellence and joins an elite global network of information management firms.”

Johnson added, “Ninestars recognizes that consumers benefit by third-party validation of service provider compliance. Under the current climate for data protection, customers’ liability is too great to be validating vendor qualifications without rigorous, audited verification.”

Ninestars has obtained PRIVACY+ Certification by complying with Data Privacy and Record Management requirements (as specified by PRISM) and by adhering to its prerequisite of obtaining SSAE 18 SOC 2 report by a certified CPA Auditor. To complete the certification, Ninestars underwent a thorough, company-wide audit, which reviewed company policies, procedures, employment records, equipment, and security. The audit examined critical areas of data security including building facility access, vendor screening, and employee background checks and drug testing.

About PRISM

PRISM International®, a division of the International Secure Information Governance and Management Association™ (i-SIGMA™), is the global body for companies providing any form of records information management services.

It serves as the educational and oversight authority for service provides offering Record Management services, and it is in that capacity that it offers its PRIVACY+ Certification program. PRIVACY+ verifies the integrity of service providers data security and financial systems, as well as their alignment with applicable regulatory. Know more here: https://prismintl.org

About Ninestars

Ninestars is a content technology company that helps organizations transform content to its true digital value. From digitization to data augmentation and analysis, our solutions are differentiated by smart technology – automation, AI, cloud-based platforms, and data science – all tuned for high performance in content-intensive businesses. Know more here: http://ninestars.in

By consistently focusing and evaluating itself against the most relevant, global standards & certification (ISO 9001:2015, ISO 2700:2013, CMMI Dev, SSAE 18 & PRIVACY+), Ninestars strives to help our clients achieve more efficient operations, improved performance, greater reach, and increased impact.

For the past couple of years we have seen organizations battling with change when it comes to digital revelations. We all have come to a stage where it is fairly obvious that accepting new technologies is not the challenge but the real struggle lies in incorporating that in your organizational DNA. This is highly proven when we see companies who started early and thus are now reaping the benefits.

So the real question looming is that what an organization can do to accelerate digital transformation in their workplaces. A few months ago Gartner specified 3 scale accelerators, which can catalyze digital transformations,

Digital Dexterity
Focusing on network effect technologies
Commercialized Digital Platforms
Let’s have a closer look at all of them,

Digital Dexterity:

Today’s business landscape calls for quick decision making, optimization of capacities, rapid change etc. all of which can only come by building a high performance digital workplace.

Digital dexterity essentially means building a flexible and agile workforce, which is motivated to put in extra efforts for your organization. Digital dexterity can be built by encouraging employee autonomy and taking efforts in creating a consumerized work environment. By providing employees with freedom rather than a controlled relationship, you get a motivated workforce, which voluntarily adds to the effectiveness of the business. Digital dexterity does not stand for a technical strategy but a long-term organizational plan and thus requires collaboration and coordination of all the departments. This will also facilitate employee’s voices being heard and quality contributions.

If you want to build an agile workforce you need to have a dynamic approach towards the way business is done. Creating a roadmap towards goals and keeping room for reassessment when those are achieved is important. This will exhibit increased adaptability. Last but definitely not the least, you need to drive your decision making based on data and have fixed metrics for what you need to know at all times. Keeping a track of these will ensure you fail fast and bounce back faster.

Building on network effects:

History proves that network effect technologies have come in to disrupt and as they have built on provided tremendous opportunities for growth. Digital transformation cannot be achieved if an organization is unable to exploit these network effect technologies as they come and creating value streams around them. The network effect technologies doing rounds, which an organization needs to look for, are, Artificial Intelligence, Internet of Things, APIs, Edge Computing, etc.

The more tightly woven business processes you build around these network effect technologies the more you have to gain from it. IoT is making the impossible possible now by connecting things which were never considered a source of information. Gaining insights from inanimate objects real time is pushing the business product portfolios to the extremes. Combining this with AI and machine learning, business functions are getting a human nature leading to various iterative functions getting automated. If we observe the companies, which have successfully built on network effects, we can say that this is just the beginning for them as they are investing in tomorrow. Trends like Edge Computing, which have pushed the ‘Cloud’ on a backseat are already creating new revenue streams for organizations like DELL.

The CIO’s and CDO’s need to scan through their resource kitty and take calls on getting the right people and systems onboard to make the best of these network effects if they want their enterprises to transform on a digital note.

Commercialized Digital Platforms

Digital platforms serve as a tool to transform the customer experiences, operational processes, and the business models of enterprises. Digital platform uses are not limited just for launching products or services but is now serving as a tool of connecting to customers in moments and providing with high-level customer experience. It is essential for companies to not look at investment in IT as costs but look at it as investment because if you want to initiate digital transformation for your company you need to put your money in digital.

We are living in the Experience economy and creating unique experiences for your customers via these platforms at any given time is going to earn you loyalty. Incorporating high end algorithms and AI with your digital platforms can enable your systems to learn with iterative approach and assist in making everything data-enabled and ensure higher level of accuracy in serving personalized solutions to your customers.

Source: Gartner

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