Wipro views Big Data as a catalyst for business transformation and enables this through our industry-focussed themes namely Business Insights, Future-ready Enterprises, Hyper-Automation and Next-Gen Products. These themes are underpinned by robust platforms and services that utilize the best-of-breed Big Data technologies across the data continuum. Our distinct PID (Process – Insights – Data) framework enables a holistic approach in addressing business transformation starting with process re-engineering through the insights layer and moving all the way down to the data and infrastructure layer. Our approach has helped our clients across industries transform their businesses and gain significantly by leveraging the power of Big Data across their value chain.
Our commitment to developing open source communities in Big Data continues with the release of Big Data Ready Enterprise (BDRE™) product to open source community establishing industry thought leadership. Wipro BDRE™ accelerates big data implementations and helps enterprises drive actionable intelligence for faster innovation.
Challenges in Risk Management can be addressed with technologies leveraging KRIs, as risk technologies will put Enterprise Risk Management more centrally in organizations
CFO's roles have evolved from being official bean counters to that of strategic partners. CFO's responsibilities & experiences make them to most suited to embrace as well as advocate technology adoption
Key trends directing future investments in Enterprise Risk Management
Wipro offers vendor agnostic approach with consistent experience across a range of Data Integration and Business Intelligence tools with predictive capabilities to overcome failures and delays during data warehouse batch runs
Money Laundering is a threat of greater than expected magnitude. The risk associated with poor AML practices cannot be underestimated simply because crime methodologies are getting highly sophisticated and need equally intelligent counter measures.
CAOs can now use data for a variety of purposes. It can help manage operational efficiencies, discover customer needs, identify new markets, give shape to new products and value-added services and develop defensible differentiators
There is an increasing recognition that CFOs and CROs are not on opposite sides of the battlefield. Instead, it is more appropriate to think of them as two sides of the same coin. But, the question to ask is how can this realization actually add value to the organization?
The arrival of the Internet of Things (IoT) introduced a new deluge of data getting processed and used for analytics
Data is the genesis for insights but the question is how value from data has indeed created protable avenues, just as it has from oil.
All forms of business management, and all studies of management science, require accurate, duplicable and reliable data at their very foundation. Big Data is helping manufacturers achieve the same.
Using advanced analytics on top of Big Data, customer data can help retail banks solve business problems by transforming their traditional data warehouses into information delivery platforms
Using insights gathered from production-data analysis, two-thirds of companies report annual savings of 10% or more in terms of the cost of quality and production efficiency.
Going into the future, a thumb rule would be to bear in mind that investments in database appliances would do better if they had a wide availability of tools – hopefully from the open source space – and were built with industry speci¬fications and standards in mind
As businesses change their processes, data structures undergo a concurrent change. This food of complex data is crippling current systems. What businesses need is robust scalability, resource optimization, consolidation and fexibility to meet even unforeseen business needs
MDM put in place tools that processes and controls reducing errors, improve data usability, enhance the quality and reliability of master data
Smart factories are the future. But they don’t have to mean abandoning your current investments in technology, data management and monitoring
Through effective and integrated data management and analysis from various manufacturing process, a significant impact can be made to various facets of manufacturing
Astute technology companies have relied upon online technical and non-technical communities to help other users with product or service features, highlight glitches, raise red ¬flags, sight early warnings, discuss performance issues, etc.
Large volume of processed data start making more sense only when it is tagged and related to the master data entities of the organization.
As the digital wave sweeps the business world, traditional approaches towards managing data are impacted significantly such that methodologies and techniques require an overhaul to support this new digital age data
Key differentiator would be an effective discovery environment that would enable rapid decision making and implementation of new offerings quickly in the longer run
Clustering techniques can also provide a better view of the customers and enable Utilities to target them better with only the relevant offers.
Using the right technology to gather real-time data from internal and external data sources and applying advanced analytics to derive real-time meaningful insights can help decision makers to shift to a more predictive mode of functioning than a reactive one.
When the CFO-CRO relationship is strengthened, we can expect to reap the benefits of operational stability, predictability of returns, enhanced reporting, increased compliance and improved profitability.
With ever increasing volumes of data, relying on data processes without a governance layer is equivalent to sitting on a bomb waiting to explode.
manufacturing industry is leveraging the Internet of Things to collect product and usage data directly and regularly rather than depend on dealers and surveyors to collect and send in the data after a machine or device has broken down
Universe of customers doesn’t have to be categorized into broad segments any longer. You can now create communication and campaigns that are CUSTOMER SPECIFIC, persuasive and produce winning results.
Cloud infrastructure is penetrating fast, and the forecast for the industry looks really sunny. Even industries known for stricter regulations on data confidentiality have embraced Cloud for a variety of processes.
A road map for transformation and rationalization that entails an unbiased understanding of the BI Inventory stack, enterprises can unlock the benefits of a cost-effective, agile and intelligent BI platform
Retailers can further enhance the in-store shopping experience through advanced video analytics, aggregate analysis of store footfalls, parking lot information and physical characteristics of store visitors to optimize product assortments.
An experienced technology partner can ensure that the business identifies the data required to be captured based on business goals and vision and prevent the risk of over inventing and over investing for retailers
Insurance fraud detection is a challenging problem, given the variety of fraud patterns and relatively small ratio of known frauds in typical samples.
Thanks to Analytics Data Discovery Platform which helps a business user to explore this data and generate insights without much training and expertise in any analytics tool
Data Envelopment Analysis is a very powerful technique to evaluate the relative efficiency of business units when multiple inputs and outputs are involved.
The benefits of targeted marketing are two-fold: one, the total cost of marketing and acquisition decreases, and two, a well targeted campaign increases the likelihood amongst target audience to respond. This leads to enhanced response rates and Return on Marketing Investment (ROMI)
Rising need of a Unified Cloud Brokerage Governance Console - a services hub - to facilitate consumption of an increasing diversity of cloud services
Paper guides you in understanding the role of analytics in optimizing Smart Meter rollouts.
Financial crime detection and prevention is critical in any organization and how augementing it with Artificial Intelligence and Machine Learning will help industries
Intelligent enterprises are being shaped by the rapidly expanding footprint of Artificial Intelligence
Real world evidence (RWE) is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of the data relating to patient health status and/or the delivery of healthcare routinely collected from a variety of sources
Machine Learning and Artificial intelligence helping Organizations enhancing data quality for better insights
Discover how to humanize AI to deliver analytics that matter?
The need to understand business performance in real time in order to manage the modern enterprise makes it important to overcome existing planning systems bottlenecks
In the digital age, digital data lakes have replaced file cabinets, and every organization is sitting on an astounding amount of data.
Harnessing advanced analytics and AI to optimize the value from IoT
With the growing client expectation of faster time to market, most of workforce efforts in the IT industry are spent in maintaining the infrastructure of the project instead of focusing on the actual work items.
Organizations are rapidly adopting advanced analytics to enable data-driven business decisions. As a result, the demand for data science experts is growing.
Amazon successfully used automation and artificial intelligence for order recommendations and fulfillment in their ecommerce platform and warehouses, but when it came to evaluating job candidates, the scoring engine failed
The Web API or API in short, is not a new technology. It has been there for more than a decade and today Programmable- Web directory lists more than 20,000 public APIs available for consumption.
The retail industry, now, has access to a wealth of data across a customer’s lifecycle. The data helps predict customer behavior, assesses needs for new products, and triggers buying decisions.
The Six Sigma methodology is not new - it has been around since the 80s. What is interesting is its long shelf life. It continues to be relevant to modern day operations despite rapid technological advancements.
A data protection process encrypts the data and removes personally identifiable information from data sets, so that the actual people whom the data
Today, AI to most businesses is a technology that aids in the automation of tasks and augments decision making by providing insights to key leaders and decision takers.
Cloud has been a great enabler in this race towards digital, building a connected cosystem that is essential to not only satiate the need of customers but also partners, vendors, employees and things.
Growing adoption of Artificial Intelligence (AI) in systems that assist, rate, and offer advice on how people are treated and what opportunities they are offered is resulting in broad discussions on how to build objective systems.
Over the years, asset-intensive industries like energy, utilities, and manufacturing have witnessed several service failures and safety incidents around machines and structures without warning.
The volume and variety of data available to organizations in the digital age is enormous, giving rise to the need of expanding their data-management infrastructures considerably and rapidly. Data lake, a new class of data-management system, holds a strong potential to achieve success in this area.
The acute need to become an insights-driven enterprise
Having the right set of processes ensure consistency in delivering promised business outcomes through intelligent systems powered by the right technology and right capability
ETL modernization with its cost-saving approaches to transactional and analytical data processing is becoming a key strategy for organizations’ IT estate rationalization
It is vital that the leadership understands the potential impact of AI across the value chain and drives the AI adoption initiative.
UDM is the driver of success for the organization that wishes to benefit from the enormous dataset (master and transactional) being hosted in any of its larger application landscape.
Product Information Management solution delivers to organizations strategic advantages that greatly enhance the digital experience of both, its internal as well as external stakeholders
DataOps helps overcome the hurdles and complexities and deliver analytics with speed and agility, without compromising on data quality
The foundation for high performance analytics
Every business needs to have a scalable, reliable model in place that addresses all business functionalities and enables understanding of business performance in real time.
IoT, 5G and AI are ushering in a new era of customer and citizen engagement.
Defining migration strategy – Defining strategy for extraction of data from different source systems, cleansing of data, validation and reconciliation of data, environment planning is very tricky and needs a customized approach suiting the project requirement.
Building smart cities and smart healthcare with edge analytics and 5G
Digital Voice User Interface will take enterprise human-machine interaction to the next level
There has been considerable improvement in use cases ranging from facial / voice / image recognition. One reason could be the abundance of labeled input data sets. We have as many photographs of human beings, cats, or dogs as we can. The more the machine can play and learn, the better it gets. The same as what happened with chess or Go.
The rapid spread of COVID-19 poses a global threat in an increasingly interconnected world.
The strategy for optimizing pricing and maximizing profits
First, take control of your data
As COVID-19 transforms the way consumers behave, it will affect demand estimation, customer targeting, and product and service fulfilment strategies.
Indian agricultural sectorpresents some staggering numbers. It provideslivelihood to 58% of India’s population with aGross Value Addition of 265.51 billion USD(agriculture, forestry & fishing combined)1. At283.37 tons, India had a record production offood grains in 2018-191.
The Private Data Privacy Act entitles Indonesia residents to even more control over their personal data. Download our quick guide to learn more.
The UK government has mandated that energy suppliers install smart metering systems across Great Britain by the end of 2024. Regulators estimate that energy suppliers will deploy 53 million smart meters during this period
Over the past decade, we have witnessed an unprecedented technological disruption in application and data functions. They are now enabling enterprise-wide digital transformation initiatives to empower customers and colleagues.
The questions on everyone’s mind
Financial institutions have been slow at adopting cloud technologies primarily due to concerns around security, regulatory compliance, and governance. As a result, they have been facing business model-related challenges like legacy technology, high running costs, and lack of scalability.
Open banking is an emerging financial technology where regulated financial institutions share some customer financial data to permit competition, innovation, and better financial products
A New Age of IP solutions Led by AI
As organizations race towards digitization, it is imperative that the underlying infrastructure keeps pace. The need for ‘anywhere, everywhere and always-on’ IT infrastructure calls for a paradigm shift in this space.
The technology landscape is full of solutions that can parse historical data, but modern businesses increasingly want to predict the future. What are the risks? What are the opportunities? Where will the market – and revenue – be five years from now? Using predictive analytics, organizations can take steps toward answering these future-focused questions.
Driving efficiency and revenue by moving beyond the scope of simple chatbots
Modern vehicles predominantly run on fossil fuels....
The 12 strategic technology trends for the coming year per Gartner shouldn’t surprise anyone; they focus on automation, security and AI. The technicalities go deeper, of course: hyper automation and autonomic systems, increased security through mesh and privacy-enhanced computation, generative AI, decision intelligence and AI engineering. But the larger issues are generally familiar. One trend is particularly familiar – the use of data fabric – because of its recurrence on Gartner’s list. Data fabric’s return is both notable and important; it underscores the need for a unified view across the democratized and ever-growing landscape of technology offerings in data storage and processing.
The prestigious Microsoft Partner of the Year awards recognize partners who have demonstrated client delivery excellence.
In response to the ever-changing digital landscape, the consumer-packaged goods (CPG) industry has directed its focus to edge computing, a distributed IT architecture transforming how businesses process data.
Today, businesses are actively exploring the potential of generative AI, engaging in use case identification, conducting proof-of-value exercises, executing pilots, and integrating the technology into their operational processes.
The Metaverse is no longer a concept confined to science fiction movies. It is becoming a reality.
ChatGPT and Bard have taken the world by storm! In many circles, even in casual conversations, discussions about the huge positive influences of Large Language Models (LLMs) and the sobering risks they pose to our socio-economic fabric are happening in the same breath.