Ness Digital Engineering Recognized as Advanced AWS Consulting Partner

Posted on 24 April 201918 August 2021 by admin

Ness is collaborating with Amazon Web Services to deliver cloud strategies that help clients achieve their digital business objectives

TEANECK, NJ – April 24, 2019 – Ness Digital Engineering, a global provider of digital transformation and custom software engineering services, has been named an Advanced Consulting Partner within the Amazon Web Services (AWS) Partner Network (APN).

Organizations that qualify for the certification must meet thorough requirements that demonstrate the scale of their AWS expertise, capabilities and engagement in the AWS ecosystem. Out of the more than 10,000 partners in the APN network, fewer than 10 percent have been able to achieve the advanced designation.

“Ness’ recognition as an Advanced AWS Partner is based on our work helping clients achieve their digital transformation roadmap through a combination of building, modernizing, sustaining, and optimizing their next-generation digital solutions using AWS infrastructure and services,” said Angshuman Patra, head of Ness’ Cloud & Platform Engineering Practice. “This partnership gives us access to additional capabilities that will accelerate the innovation we can bring to our customers, and we want to become the digital engineering partner of choice for the AWS ecosystem.”

Ness’ digital platform engineering services leveraging the cloud include the following:

Advisory & assessment services for cloud adoption
Application workload migration to the cloud, including re-hosting, re-architecting, and re-platforming
Cloud native application development
Cloud monitoring and optimization services
Big Data & Analytics and Internet of Things (IoT) data processing at the edge and in the cloud
DevOps development processes

Ness is also investing in expanding its offerings using AWS around conversational experiences and augmented reality / virtual reality (AR/VR) in the cloud.

About Ness Digital Engineering

Ness Digital Engineering designs, builds, and integrates digital platforms and enterprise software that help organizations engage customers, differentiate their brands, and drive profitable growth. Our customer experience designers, software engineers, data experts, and business consultants partner with clients to develop roadmaps that identify ongoing opportunities to increase the value of their digital solutions and enterprise systems. Through agile development of minimum viable products (MVPs), our clients can test new ideas in the market and continually adapt to changing business conditions—giving our clients the leverage to lead market disruption in their industries and compete more effectively to grow their business. For more information, visit ness.com.

Media Contacts

Amy Legere
Greenough
alegere@greenough.biz
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Vivek Kangath
Senior Global Manager – Corporate Communications
Ness Digital Engineering
Mobile: +91 9742565583 | Tel: +91 80 41961000 | DID: +91 80 41961027

Amazon Redshift: Vendor Lock-In Never Felt So Good

Posted on 19 April 20197 June 2021 by admin

The Hadoop ecosystem has a well-known hole: there is no good opensource tool for near-real time analytics on Big Data. For example, suppose you have 500 milliseconds to calculate the average temperature reading from a set of sensors, based on some ad hoc user-specified criteria such as location, time and sensor type. Pre-aggregation is not feasible, because you cannot anticipate what search criteria the user will specify. Hive is too slow, even when it runs on Tez in Hadoop 2.0. Cloudera’s Impala may be fast enough, but it makes so many assumptions about what it can fit in memory that it is notoriously unreliable.

Amazon Redshift is meant to fill that hole by handling analytic workloads on large scale datasets in near real time. Redshift is built on top of the ParAccel analytic database, designed by a brilliant serial entrepreneur (and ex-colleague of mine at Applix) named Barry Zane. ParAccel was based on the following principles:

Start with Postgres and add analytic extensions. By using Postgres as the foundation, ParAccel benefited from a well-developed ecosystem of tools, e.g., for ETL and query optimization. ParAccel then extended SQL with mathematical, statistical and data mining functions, as well as a language for creating user-defined functions.
Support columnar orientation for tables. In row format, all the columns for a given row are stored consecutively on disk. This is great for transaction processing, since updating a single row requires only one I/O operation. But, it is not so great for analytics, which typically processes a single column value for all rows. In row orientation, this requires one I/O operation for every row. In columnar orientation, on the other hand, all values for a given column are written consecutively to disk. This is not so great for transaction processing, since updating a row requires one I/O operation for every column in the row. But, it is ideal for analytical processing, since a typical analysis can be satisfied via a single read of all values for a single column.
Base the architecture on Massively Parallel Processing (MPP), with a shared-nothing architecture. The leading cause of poor database performance is contention over shared resources, such as table rows or memory. An MPP architecture avoids these bottlenecks by sharding the data over multiple servers, so that each server has all the resources and information it needs in order to perform most queries. Other databases such as Teradata and Greenplum are based on MPP, but ParAccel succeeded in making its MPP more robust than most of the others.

Amazon took ParAccel and adapted it to the cloud by adding features such as elasticity, so that the database cluster automatically scales up to handle demand bursts. Amazon then slapped on a very aggressive price tag of only $1K per terabyte per year, a fraction of the total cost of ownership for alternatives such as Teradata, Netezza and, yes, even Hadoop. The total managed offering was re-branded as Amazon Redshift.

The result is a game-changer for data warehouses. Suddenly Big Data Analytics is available to small and mid-sized organizations, who cannot afford to purchase and manage any of the alternatives. It cannot do everything the alternatives can do (e.g., it cannot handle petabytes of data like Hadoop), but it completely undercuts the alternative solutions by trading away generality for price. It can also serve as a complementary technology to Hadoop by filling in Hadoop’s missing capability for near-real time analytics on Big Data.

And yet, I am hesitant to recommend Amazon Redshift to Ness’s Big Data customers, unless there is no other good Open Source alternative. The reason: I am afraid of vendor lock-in. No one is better than Amazon at making vendor lock-in feel so good. The price is great, and you’ll never have to worry about provisioning, database maintenance or version upgrades.

But, let’s be clear – choosing Redshift locks you in to Amazon, because once you develop your queries using Redshift’s dialogue of SQL, you will find it impractical to switch to anything else. Yes, the terms offered by Amazon are extremely reasonable, but high tech is replete with stories about victims of captive pricing, who are forced to pay whatever updated price the vendor demands, because there is no alternative.

I once experienced firsthand the dangers of captive pricing. My start-up company needed a map widget for our web site, and we could choose either Google’s free widget or a competitor’s commercial widget. Free seemed like a good price, so we went with Google. Just as the web site started to grow in popularity, we received an email from Google telling us that, effective immediately, their map service would no longer be free, but would cost twice as much as the competing service. We had no choice but to pay the fee because the alternative would have been to shutter the web site just as it was gaining popularity.

I’ve never forgotten that feeling of having been taken in by attractive pricing, then discovering I had no choice but to pay a much higher price. So, when analyzing a customer’s problem, I always try to find a reasonable Open Source alternative to Amazon Redshift. Sometimes, when there is no good alternative, e.g., when the use case demands near-real time analytics, I recommend Redshift, because it is a fine product with a fine price. But, I also tell the customer that there are no guarantees that the pricing terms will remain so attractive down the road.

Nessathon 2019- Gear up for the real challenge!

Posted on 16 April 201928 May 2021 by admin

Ness Digital Engineering will be conducting Nessathon 2019—A Hackathon for technical minds across the Mindspace office complex, Mumbai on May 11^th, 2019. The Nessathon is aimed at bringing technology geeks under a common roof to show off their technical skills. Take the challenge of the Nessathon and come up with creative solutions to solve problem statements.

Ness: Changing the Way People Do Business in the Digital Economy

Posted on 12 April 201928 May 2021 by admin

Accelerating digital transformation.

Ness designs and builds digital platforms and software that help organizations engage customers, differentiate their brands, and drive revenue growth.

Delivering Services- Between Empathy and Automation

Posted on 11 April 20197 June 2021 by admin

When it comes to delivering services, Agilists embrace the idea of working in iterations which deliver value to their client after each cycle of about two weeks. When tackling a new idea, a coherent bundle of initial iterations is called Minimum Viable Products or MVP and promises a usable digital product that can be ideally presented to the client’s clients. This perspective on product delivery is part of the culture of companies leading the digital transformation. There’s more to these ideas though. Adopting methodologies suitable for digital transformation require capabilities to sustain the higher cadence. When reading about leaders in digital you are likely to find teams who:

have an empathy for the end-user and an approach to engineering an experience which goes beyond drawing wireframes
have adapted their toolchain to churn out stories without compromising overall quality and technical debt
have established a product evolution culture, building what is required and improvise. The digital transformation will expose users more and more to service touchpoints in situations which would have been hard to predict just a few years ago. Take for instance a large retail company’s use of Conversational User Interface (CUI) technology and machine learning to improve customer experience with voice and image search. Taking a user journey approach becomes essential to map the activities and derive meaningful stories, which form a whole that is immediately put to the test and generates valuable feedback for the next iteration. This approach ensures MVP stakeholders, who don’t know what they don’t know, address their actual user’s needs.

Delivering quality code against the stories selected for the Sprint (an Agile iteration in Scrum) involves often a larger number of software engineers but also UI designers, data scientists, DevOps and other contributors. Coordinating work requires the appropriate harness before the first lines of code is written. A number of practices exist which allow work in distributed fashion across time zones without sacrificing overall system quality attributes. What’s more, engineering excellence is backed by operational excellence which embodies the governance for orchestrating the multiple moving parts found in transdisciplinary projects. Delivering projects at fast pace to ensure valuable releases at each iteration involves data-rich project tracking while empowering team members with the right amount of discretion to decide how to progress in their daily activities. A departure from more traditional management approaches which is even shaking some traditional structures such as the military as shown in Gen. Stanley McChrystal’s book “Team of Teams”.

The combination of these two postures gives organizations a higher chance of succeeding in the digital transformation to leverage advances in, say, connected devices, predictive analytics, or indoor positioning. At Ness, we have the privilege of working with innovative companies for over a decade, including some leaders in the information economy who contribute directly to technology and methods. This cumulated knowhow goes to traditional organizations for a successful transformation towards the digital economy.

CIO Jury: Why 58 percent of tech leaders are unprepared to handle IIoT data

Posted on 9 April 201918 August 2021 by admin

Moshe Kranc, CTO of Ness Digital Engineering, has been featured in ZDNet. In the article, “CIO Jury: Why 58 percent of tech leaders are unprepared to handle IIoT data,” Moshe shares his thoughts on what organizations need to be able to collect and correctly process Industrial IoT data.

“Many organizations lack data governance processes needed to ensure the quality of collected data, as well as the in-house skills to create a system to process near real-time streaming big data, or data scientists who can extract insights from this information, said Moshe Kranc, CTO of Ness Digital Engineering.

Click to view full article: https://www.zdnet.com/article/cio-jury-why-58-percent-of-tech-leaders-are-unprepared-to-handle-iiot-data/

Perspective from the Field: Digital Disruption Is Becoming Mainstream

Posted on 4 April 20199 August 2021 by admin

Digital transformation is changing the way we consume goods and services, digital disruption is becoming mainstream. Out of the top 10 most valued companies (based on market cap) in the world, the top 4 spots are taken by born digital companies or companies that are at the forefront of digital transformation. There is hardly any industry which is not disrupted by the digital wave. The 2019 Gartner CIO Agenda survey reveals that “digital businesses reached a tipping point in 2018” and 49% of CIOs surveyed say they have transformed or are in the process of transforming their business models. Many businesses have started their journeys to unleash new products and services digitally, and they also need to be ready for the next great shifts in technology cycles, competitor actions, and customer requirements. Businesses can no longer afford to waste their time and resources on long product development cycles when customer needs and competitive threats can change so quickly now. Anticipating the next big disruption and preparing for it is one of the best ways for companies to stay relevant to their customers.

How companies are preparing to improve their positions in the ‘Digital Economy’

As organizations look to embrace the benefits of the digital era, we’re hearing some common themes among customers as they focus on enhancing their positions in a Digital Economy:

Increasing Utilization of Data and Metadata: The idea of using data (such as data within and outside the enterprise, structured and unstructured data, data generated by machines, and online and mobile data) to create business value is not new; nevertheless, the effective utilization of data is becoming the basis of new competitive battlegrounds. Businesses want to better utilize data and metadata to glean rich insights about their customers’ behavior and purchase patterns, so they can outsell competitors by offering more personalized product recommendations and a more “friction-free” buying experience. For example, a telecommunications company is leveraging Ness’ competence in Artificial Intelligence and Machine Learning (AI/ML) to help the company predict (and prevent) potential customer churn. The solution not only helps prevent customer churn, but it also improves the customer experience based on the rich insights it derives using AI/ML models
Sharp Focus on Cloud to Increase Flexibility and Scale: Cloud is now an integral part of any enterprise digital journey because it enables businesses to be nimbler and respond faster to market opportunities. Using the Cloud also enables businesses to offload basic technology infrastructure management to the cloud company, so they can focus more time on what’s core to them. Companies want our help to modernize and move their applications to the Cloud, and we are also seeing greater demand for Platform as a Service (PaaS) and Software as a service (SaaS) offerings. Companies are also looking to the Cloud to experiment with AI/ML technologies in a much more cost-effective manner.

Expansion of Automation: Increased automation across the technology landscape, including development, provisioning, and operations for both on-premise and cloud-based systems, can also help deliver the speed, agility and cost benchmarks companies want to achieve. For example, process automation can help businesses realize the benefits of scalability and speed, while maintaining complete operational control. In the near future, we expect to see Robotic Process Automation (RPA) playing a significant role in digital business. In addition, RPA providers are integrating AI/ML functionality into their product suites to identify, optimize, and automate labor-intensive and repetitive activities that are currently performed by humans. IDC predicts that by 2024, AI-enabled user interfaces and process automation will replace one-third of today’s screen-based apps. By 2022, 30% of enterprises will use conversational speech tech for customer engagement.

Increasing Adoption of AI and ML: Companies are exploring AI/ML applications not only for customer-facing applications, but also for internal company applications to enable more seamless operations. According to Gartner’s CIO Agenda 2019, 7% of top-performing companies ranked artificial intelligence (AI) as a game-changing technology in 2018. This year, the number will be drastically increased to 40%. What once started as rule-based automation is now capable of mimicking some human actions. This can help employees complete their work with increased productivity.

Translating plans into action

The digital technology landscape offers a plethora of choices. Many companies tell us that deciding which digital transformation platform to invest in is particularly challenging. Ness will often facilitate “Discover and Envision” sessions with clients to help them identify and prioritize their digital transformation initiatives. For example, we helped a traditional media company create a robust OTT platform for rendering premium content to which it has exclusive rights. Ness helped the company reimagine the entire customer experience to develop a differentiated platform right from the beginning. As a strategic partner to our clients, we are always excited for the opportunity to help our clients break through legacy thinking and find future growth opportunities.

The success of any digital transformation strategy lies in making right choices, which include selection of the right digital platforms, tools and technologies; and more importantly, the right services partner who can help execute digital vision into a reality.