Until a few years ago, there was an accepted nature of the interactions between BPCL and its customers. There was no unified view of the company from the customer鈥檚 perspective 鈥� for example a fuel customer had little idea of the LPG or lubricant business, while the company did not have visibility into the customer鈥檚 holistic energy needs. The digital transformation initiative aimed at changing this customer experience based on the three pillars of trust, convenience and personalization.听听

Raman Dhillon, Head of Digital Transformation at BPCL says, 鈥淭oday鈥檚 customers expect the same kind of a user experience from us as they would from a Netflix or Amazon, where things happen at a single touch without hassles. We need to step up to deliver this across our touchpoints with them.鈥� The belief of the project was to keep the customer experience front and centre, giving a single window view into BPCL鈥檚 offerings and enabling transactions in a trusted, secure and personalized environment.听

Bharat Petroleum Corporation Ltd (BPCL) – Drivers of Digital Transformation

At the leading edge of this initiative was the Hello BPCL app, that presents a unified super-app style of functioning to access fuel services, LPG services, lubricants and more to a customer. For example, to address customer issues of trust at fuel stations, the app allows you to pre-buy a certain value of fuel and pay for it digitally. Once at the fuel station a simple QR Code scan loads the fuel value into the system, leading to a seamless experience with no human intervention. Another area of customer confidence building was with the fluctuations in fuel prices. In a volatile fuel price market, customers are naturally anxious whether they are being charged the correct rate. Nozzle-level technology at BPCL鈥檚 fuel stations ensures that if there is any discrepancy detected in the fuel price loaded on the system the nozzle is automatically deactivated. The technology layer required to bring these changes to life reflects the commitment to the customer鈥檚 experience and enhance their quality of interactions with the company.听

Riding on the comprehensive, yet flexible omnichannel strength of the 51风流Commerce Cloud, BPCL reimagined its customer journeys across different persona types to digitally transform the customer experience. It began engagement with business leaders at over 400 workshops where the teams aided by 51风流functional experts shaped the technology and processes for better customer-centricity. But in order to deliver this experience, it was important that the supply chains were also totally integrated, with a real-time view. This led to the birth of the command control centre, called IRIS 鈥� a single system to monitor and control all BPCL assets, enabling safety, security & compliance and most importantly, flawless customer experience. The teams re-created seamless processes for customer onboarding, ordering, payments, fulfilments, etc. across omni-channels environments like mobile apps, websites, etc.听听

Enhancing the CX Transformation Journey

听鈥�In the process of crafting the customer experience transformation journey, the role of 51风流has been extremely important. We got all necessary support to ideate and implement the right solutions to achieve this scale. This partnership will be remembered for a long time鈥�, acknowledges Mr. Dhillon. The 51风流team found this engagement enriching as well.听 鈥�BPCL is spearheading an innovative approach towards easing the lives of Indians and building the nation,鈥� says Sudeep Singh, Vice President and Head of CX Business, 51风流Indian Subcontinent. 鈥淲e are privileged to collaborate with BPCL in its journey to enhance customer experience and also boost the vision of 鈥楧igital India鈥� at scale.鈥�听

Future of CX Transformation

The future holds exciting promise for a digital journey of such epic proportions. Plug-n-play cloud solutions, EV charging stations, regional language enabled chatbots that cover over 600 customer scenarios are all initiatives that are set to push the envelop forward.听听

For 51风流partnerships the integrated Customer Experience (CX) is one of the key levers of digital transformation. It is a fusion of channels, such as retail outlets, customer service desk, self-service kiosks, online chat, chatbots, personalized physical robots or virtual assistants. Companies like are transitioning from brick-and-mortar to omnichannel businesses, empowering customers with its digital initiatives to ensure a seamless, trust-positive, convenient and personalized shopping experience.听

The post Bharat Petroleum: Redefining Customer Experience Transformation appeared first on 51风流India News Center.

Given the kind of data-centric world we are heading for, organizations need to take extra care while integrating and migrating data on the cloud.

Cloud-based data migration is simply the process of moving enterprise information and infrastructure from on-premise to cloud computing infrastructure. This involves transferring data, workloads, applications, etc. One area which is steadily gaining traction is cloud data warehouse. Today,听听boast of workloads in the public cloud. Think of a as a database that is primarily used to tackle explosive data growth while storing information from a wide variety of sources, including Internet of Things (IoT), CRM, and so on.

Why is Data Migration Necessary?听

From new system implementations (think: ERP, CRM, etc.) and mergers & acquisitions to system rationalization and the need for reduced costs, there are multiple reasons why organizations may choose to migrate their data to the cloud. Without real-time, accurate data at hand, enterprises are at a decided disadvantage.

A key enabler of data-driven decision-making, cloud-based data migration can offer a host of business and operational benefits such as:

• Increased scalability, integrity reliability, and security of data with stringent compliance of policies
• Reduced IT costs when compared to cost-intensive on-premise costs such as hardware, software, support, downtime, depreciation cost, etc.
• Environment-friendly, 鈥榞reener鈥� alternative to on-premise systems and increased energy savings due to reduced need for physical materials for setup
• Increased speed-to-market when delivering projects
• Maximized uptime while backing up data, recovery, and system upgradation, ensuring business continuity
• Easy data availability on-demand leading to increased business agility
• Greater opportunity to leverage newer technologies such as machine learning, artificial intelligence, etc. and drive innovation
• Increased productivity due to consolidated data centers and the ability to outsource data management capabilities to a third party, allowing enterprise resources to focus on more high-value tasks
• Accelerated digital transformation and organizational growth as CTOs and leaders can opt to digitize core functionalities easily and seamlessly
• Better product delivery that is aligned with the user鈥檚 needs as the team focuses more on the user experience instead of constantly struggling with the data

Top 7 Cloud Data Warehouse听Best Practices听for Migration Success

1. Involve all departments of the organization instead of making it an IT-only job.

Most enterprises view data migration as the sole responsibility of the IT team鈥揳 big mistake. To drive migration success, consider the 鈥榟uman element.鈥� In other words, enterprises need to engage in behavioral management and involve all stakeholders across the board at all stages of data migration. This can be done by driving stakeholder participation and ensuring that the key resources are always available during the migration process. Doing so can throw light on hidden issues early on in the project and take the guesswork out of the equation.

The reason:

In reality, data migration failure is not always hardware- or software-dependent; it is behaviorally driven and a collective effort. Enterprises need to relook at their data migration process via a collaborative lens and ensure that every team is on board.

2. Plan extensively to understand the ideal cloud-migration approach.

Instead of viewing the data migration process as an isolated event that involves moving data from point A to point B, view it as a continuum of moving parts working together to enhance organizational performance and competitive edge. Simply put, there needs to be a greater effort in the 鈥榩lanning鈥� stage to ensure that enterprises:

• Benefit from an end-to-end, repeatable process flow
• Understand the best-associated methodology and approach for data migration
• Engage in a cost-benefit analysis to integrate a pay-as-you-go model instead of paying for additional infrastructural costs

The reason:

There are numerous types of cloud migration strategies that enterprises can adopt depending on their size of business and data complexity. Some of the most common strategies include re-hosting, re-platforming, re-architecting, re-purchasing, and retiring. Without proper planning, organizations will not be able to understand their existing IT environment and the kind of cloud vendor to choose to advance their data migration goals. Additionally, it can lead to prolonged downtime due to a chaotic data migration process, eventually costing organizations $5,600 per minute, according to estimates by听.

3. Engage in data profiling

Data profiling is essential for two reasons. One, it helps uncover risk early on. Two, it empowers enterprises to understand the data inside out fully. Moreover, using the profiling results gathered, stakeholders can be engaged across diverse aspects such as:

• Driving root cause analysis to identify business process flaws within the data
• Having empirical discussions about the data state
• Driving discussions on prioritizing requirements that are essential versus 鈥榥ice to have鈥�
• Identifying and analyzing inconsistencies in the data between the environment鈥檚 documented state and the true state
• Gauging the level of effort required to ensure that the data is fit for the prioritized purposes

The reason:

Accurate estimates about the time and effort required cannot occur without data profiling at the beginning of the migration process. In other words, if you want to successfully migrate data without letting guesswork get in the way, data profiling is necessary.

4. Build a culture of data governance

Data migration is as much about the people and processes engaged in the process as it is about technology. To cater to the 鈥榟uman鈥� factor of the data migration aspect, ask the following questions before deep-diving into the data migration process:

• Which resources need to be involved?
• What do 鈥榞ood data鈥� and 鈥榙ata duplicate鈥� constitute?
• What to do when remediating a data quality exception?
• What does the escalation process look like if a decision cannot be made?
• How to deal with the initial spike of remediation needs versus the steady state?
• How to ensure data quality after going live?

The reason:

To effectively manage data governance, leaders need to ask these questions and devise a strategic plan鈥搊ne that aims at establishing a culture of data governance from top to bottom within the organization, and caters to the needs of the end-user as well as the internal stakeholders.

5. Pivot as needed and embrace change

As organizations get more visibility into the data, iterations may be required at every step of the data migration flow. This lowers risk and improves the quality of the final output. It also doubles up as an opportunity to add cleansing rules with every iteration. As a thumb rule, organizations should iterate as often as needed. The end goal is to embrace change as readily as possible.

The reason:

Leaders need to focus on strategizing ways to help drive 鈥榗hange management.鈥� In simpler words, this translates to enabling people to readily embrace the changes in adaptability by:

• Training employees on the new system
• Designing, implementing, and monitoring a plan to support鈥揳nd back up鈥搕he change keeping in mind the end-user and the team鈥檚 needs

6. Segregate the data from the application

Most organizations make the mistake of not separating the distinct needs of the data and the application. While these two may be connected, they have individualized requirements. Another key area of concern is rushed application and data assessment, where enterprises do not completely assess the workloads. This leads to a skewed understanding of which migration approach to undertake for the specific data and applications.

The reason:

Without segregating the data from the application, there will be blind spots and 鈥榦verlooked data鈥� within the architecture. Plus, data segregation also helps to understand the remediation aspects to undertake for the project. Finally, it empowers enterprises to understand the specific migration requirements and eliminate the chances of scope creep.

7. Select the right cloud provider with security of data as a key focus point

When it comes to finding the best fit for migration support, tools, safety, or approaches, selecting the right cloud provider is paramount. Companies should investigate whether the cloud providers have the necessary data migration tools to move data by considering factors of vendor lock-in and portability.

Think of it as 鈥榚xpectation management鈥� between the two parties involved by having proper written and authorized documents鈥搊r an SLA (Service Level Agreement鈥揳s it is commonly known. Considering that most organizations would want to outsource their infrastructure services to the cloud providers so that they can focus on the core business, selecting the right cloud service partner can allow for better strategic business goals alignment as well as profitable outcomes.

The reason:

Most CTOs opt for a migration partner based on low pricing or familiarity instead of factoring in 鈥榚xperience.鈥� This can lead to mistakes and rework, causing your cloud migration costs to go off the rails. In addition, there are increasing concerns with respect to security protocols between the client and cloud providers, leading to the inevitable 鈥榯rust deficit.鈥� Finally, if the vendor does not plan and execute the security protocols properly, data breaches will become an everyday issue, costing the enterprise millions.

The Bottom Line

Data migration will continue to gain momentum with the global public cloud spending poised to exceed $480 million by 2022, according to听. Clearly, not building a roadmap for the data migration journey is already ensuring that the organization is set up for failure. After all, moving data from legacy to cloud is not a simplistic, linear approach.

To help drive better decisions and deliver a safe, cost-effective, and results-oriented data migration process, sticking to the best practices outlined above can make the process simpler, more streamlined, and scalable while being cost-effective.

The post The Ultimate Guide to Cloud Data Warehouse Migration appeared first on 51风流India News Center.

What is Big Data?

Big Data is a term that refers to large volumes of hard-to-manage data that inundate businesses on a day-to-day basis. It also refers to the field that deals with ways to analyze and systematically extract information or just deal with data sets that are too large or complex to be dealt with by traditional data-processing software.

The challenges to big data analysis include data capture, data storage, search, sharing, transfer, visualization, querying, updating, privacy, and data source. The complexity of big data makes it impossible to process using traditional methods. The concept of big data gained momentum in the early 2000s when Dough Laney defined big data as the three V鈥檚- Volume, Velocity, and Variety.

Volume

Organizations collect data from a variety of sources and storing all of those data would have been too costly if not for new and cheaper alternatives like data lakes, Hadoop and the cloud.

Velocity

Internet of things warrants timely processing of data streams traveling at unprecedented speeds. These torrents of data need to be dealt with at near-real-time speeds.

Variety

Data can be of many types 鈥� structured numeric data in traditional databases to unstructured text documents, videos, audios, financial transactions etc.

Big Data in the present context

Big Data is synonymous with predictive analytics, user behavior analytics, or other advanced data analytics methods that extract value from big data. We rarely refer to a particular size of data set when big data is mentioned. The relevant characteristic of this new data ecosystem is to find new correlations to spot business trends, prevent diseases, combat crime and more.

The advent of widespread technology, including mobile phones, has tremendously increased the size and number of available data sets. Internet of Things (IoT) devices, aerial sensing, software logs, cameras, microphones, Radio Frequency Identification (RFID) and wireless sensor networks are just a few of the many cheap and numerous information sensing devices that add to the data pile.

Applications听of Big Data

The increasing use of data-intensive technologies by developed economies has spurred the demand for information management specialists and data analysts across the globe. Between 1 billion and 2 billion people are accessing the internet and there are 4.6 billion mobile-phone subscriptions worldwide.

• Government Use of Big Data

Big data use in government processes allows efficiencies in cost, productivity and innovation. But it does have its flaws; for instance, the听听to search for patterns that have the potential to lead to illegal activities. Privacy is an aspect that is still being debated in the context of big data.

• International Development

Big data offers cost-effective opportunities to improve decision-making in critical development areas such as health care, employment, economic productivity, crime, security, natural disasters and resource management. User-generated data is also an avenue for the unheard to be heard. However, technological infrastructure and economic and human resource scarcities remain challenges to developing regions. These scarcities can potentially exacerbate existing big data concerns like privacy, imperfect methodology, and interoperability.

Big data has been significant in the fight against poverty by providing satellite imagery and machine learning for poverty prediction. For instance, the labor market and the digital economy were studied using digital trace data in Latin America.

• Healthcare

Big data analytics plays a significant role in healthcare through:

• Personalized medicine
• Prescriptive analytics
• Clinical risk intervention
• Predictive analytics
• Waste and care variability reduction
• Automated external and internal reporting of patient data
• Standardized medical terms and patient registries

Human inspection is impossible at the volumes of big data scales, and intelligent tools for accuracy, believability control and handling of information are required. These are conducted with the help of specific analytic tools. Data-driven analysis has helped in exploratory biomedical research as it can move forward faster than hypothesis-driven research. Computer-aided diagnostics is another aspect of healthcare that depends heavily on big data.

• Media

By providing actionable insights into millions of individuals through big data, a message or content that aligns with the consumer’s mindset can be conveyed. Consumers are tapped into with the help of targeted content that reaches people at optimal times in optimal locations. The current advertising ecosystem is a good example of this.

• Internet of Things (IoT)

The media industry, companies, and governments use the data extracted from IoT devices to accurately target their audience and increase media efficiency. The sensory data gathered from the devices are used in medical, manufacturing and transportation contexts. Ideally, the data from devices would help track and count everything and tremendously reduce waste, loss and cost.

• Information Technology

Big data has helped business operations as a tool to streamline the collection and distribution of Information Technology and improve employee efficiency. Deep computing and machine intelligence help IT departments predict and prevent issues.

• Machine Learning and Artificial Intelligence

Big data is a crucial component used in the training of complex models and facilitating Artificial Intelligence.

What is Cloud Computing?

It is the on-demand availability of computer system resources like data storage and computing power without direct active management by the user. Large clouds often have their functions distributed over multiple locations, with each location acting as a data center. Reliance on sharing resources to achieve coherence is a characteristic feature of cloud computing.

Cloud storage makes it possible to save files on a remote database instead of a proprietary hard drive or local storage device.

Types of Cloud Computing Services

Cloud computing services provide users with a series of functions including:

• Email
• Storage, backup, and data retrieval
• Creation and testing of apps
• Data analysis
• Video and Audio Streaming
• Software on demand

Benefits of Cloud Computing

1. Increased productivity, reduced costs, speed, efficiency, performance, security, and portability are just a few of the reasons why Cloud Computing has seen an increase in popularity lately. The heavy lifting involved in processing data is done by the remote system instead of the device that a person carries to work.
2. Being a fairly new service, cloud computing is used widely in the business space by big corporations, small businesses, non-profits, government agencies and even individual consumers.
3. Before cloud computing, businesses were required to purchase, construct and maintain costly information management infrastructure. Now companies can swap costly server centers and IT departments with fast internet connections over which employees can interact with the cloud to complete their tasks. This has resulted in tremendous cost and time savings.
4. Reliance on tangible software upgrade methods like discs and flash drives is replaced by faster methods of internet upgrades. It also helps individuals save storage space on their desktops or laptops through customer data cloud services.

Cloud Computing Concerns

1. Security has always been a natural concern when it comes to sensitive medical records and financial information. Encryption protects vital information, but the loss of the encryption key would result in data loss. The issue of security in cloud computing is an ongoing issue, with regulations forcing service providers to shore up their security and compliance measures.
2. Then there is the issue of server damage. For instance, a server company can fall victim to natural disasters, internal bugs, power outages and more. A blackout in one part of the world could affect the users accessing that data from another country.

Big Data on The Cloud

Big data before the cloud strained the financial and intellectual capital of even the largest businesses by the sheer amount of computing resources and software services needed to support the effort. With the advent of cloud computing technology that provides almost limitless computing resources and services, big data initiatives are now possible for any business, big or small.

Enterprise Case Studies for Big Data on the Cloud

• Netflix on AWS

Being one of the largest media and technology enterprises in the world, Netflix stores billions of data sets in its systems concerning audio-visual data, consumer metrics and recommendation engines. AWS gave the company a solution that would allow it to store, manage, and optimize viewers鈥� data and offered a platform that would enable quicker and more efficient collaboration on projects. It enabled Netflix to discover and respond to issues in real-time, ensuring high availability and a great customer experience.

• 2. mLogica on 51风流HANA Cloud

mLogica, a technology and product consulting firm, wanted to move to the cloud to better support its customer’s big data storage and analytics needs. 51风流HANA Cloud enabled the move from on-premises infrastructure to a more scalable cloud structure. It helped them to manage growing pools of data from multiple client accounts, improve slow upload speeds for customers, move to the cloud to avoid maintenance of on-premises infrastructure and integrate the company鈥檚 existing big data analytics platform into the cloud.

Advantages of Big Data in the cloud

• Scalability

The physical constraints of a typical business data center significantly throttle its ability to conduct business. A public cloud negates the space, power, cooling and budget requirements of a big data infrastructure by managing hundreds of thousands of servers spread across a fleet of global data centers. It also translates to savings in time as the cloud infrastructure is already built and ready to go.

• Flexibility

Businesses can choose to employ the required number of servers according to the budget and task at hand, and then later release them when the task is complete.

• Cost

Hardware, facilities, power and maintenance are just a few of the expenses for building and maintaining a business data center. The prohibitive cost and wastage are removed through a flexible rental model where resources and services are available on-demand and follow a pay-per-use model.

• Accessibility

The significant global footprint of cloud services enables resources and services to be deployed in most global regions. The data and processing activity can take place proximally to the area where the big data task is located instead of moving that data to another region.

• Resilience

Replication of cloud data across its servers is standard practice by service providers to ensure high availability in storage resources and maintain cloud data resilience.

Cons of Big Data in Cloud Computing and Ways to Overcome them

Even though the value of big data in cloud computing is tremendous, it鈥檚 not without its pitfalls. Businesses need to consider potential drawbacks before adopting a public cloud or a third-party big data service.

• Network Dependence

The effect of outages is a significant concern in any big data use of the cloud. Cloud use requires complete network connectivity from the LAN, through the internet, to the cloud provider鈥檚 network. An outage at any point in this chain could result in increased latency at the best of times and complete cloud inaccessibility at worst. Data replication and usage of reliable networks and cloud services can reduce this risk considerably.

• Storage Cost

Data storage can be a substantial long-term cost for big data projects on the cloud. The loading of data into the cloud is time-consuming and the storage instances incur a regular fee. Data migration, which refers to the transfer of data between servers, may incur additional fees and loss of time. Hence, comprehensive data retention and deletion policies must be employed by businesses to prevent retaining unnecessary data and deal with time-sensitive big data sets.

• Security

The data involved in big data projects can contain proprietary or personally identifiable data that is subject to data protection laws and other industry or government-driven regulations. Security of such data is paramount. Cloud users must take the steps needed to maintain security in cloud storage and computing through adequate authentication and authorization, encryption and copious logging of access and usage of data.

• Lack of Standardization

As there is no single way to implement and operate a big data deployment in the cloud, there is a potential for poor performance and exposure to security risks. Documentation of big data architecture, along with policies and procedures of use, should be prioritized by business users to sidestep potential problems. This documentation can become a foundation for future optimizations and improvements.

Choosing the right customer data cloud provider

Even though the underlying hardware gets the spotlight, it鈥檚 the analytical tools that make big data analytics possible. Providers such as听听can arrange for support and consulting to help businesses optimize their big data projects so that they won’t need to start their initiatives from scratch.

The post How Big Data Needs of Businesses are Transformed with Cloud Computing? appeared first on 51风流India News Center.

The key reasons to move to the cloud include:-

1. Agility- As per a听, the agility of an organization has become more important due to disruptions like Covid and supply chain issues. An organization that can reinvent its business model has a much higher chance of staying relevant in an increasingly complex, ever-changing world. By moving to the cloud, you can get the required platform, infrastructure, and computing capability to become agile.听
2. Lower costs- One of the most significant benefits of moving your system to the cloud is the accrual of cost benefits because of the following reasons: –
   1. No requirement of a dedicated server- Your hardware demand for storage becomes linked to your scale of business. You will no longer own physical storage. You can scale as and when your business scales to pay as you go rather than spending upfront on a dedicated server.
   2. Lower energy costs- It is well known that idle servers consume electricity, and when you store applications on the cloud, you no longer need to pay for idle servers.
   3. Lower workforce costs- Maintaining a data server requires high-quality IT staff, which is expensive. If you move to the cloud, you don鈥檛 need dedicated staff to maintain your data server and it is effectively outsourced to the cloud service provider.听
   4. No upfront costs- Setting up a dedicated server requires upfront costs. These upfront costs can disrupt your cash flow. Whereas, if you spend on a cloud-based infrastructure, you can pay as per the requirement without any upfront commitment from your side, thus making your organization more adaptable to change as per the requirement of IT infrastructure.听
3. Security- As per听, 94% of cloud adopters believe it to be more secure. Benefits range from a lower risk of data breach and less chance of system shutdowns or system failures.听
4. Faster Prototyping-听Being able to develop a prototype at a rapid pace and test its success will help organizations decide whether they want to go ahead with implementation. A cloud-based IT infrastructure can help the organization prototype and test the changes faster. This can make an organization more nimble by reducing the time to change.听

Despite all the apparent advantages of cloud-based IT infrastructure, as per听, only 50% of all corporate data is stored in the cloud as of July 30, 2021. This has increased from 30% in 2015. If you want your organization to successfully migrate most data to the cloud, you require coordination of different teams and particular focus from the CIO, CTO and CEO. To ensure business transformation on the cloud, the听following steps听should be considered to get a robust and efficient system that can continue in the future as well: –

1. Establish Responsibilities- Before migrating your data to the cloud, make sure your team understands the responsibilities and chief architects of the change. Such a team will be set up on consultations with the CEO, CIO and CTO, the key stakeholders and decision-makers in the cloud migration journey. This team should now be responsible for planning and executing the migration. Migration priorities and benefits should be established after due consideration.听
2. Shallow cloud integration v/s Deep cloud integration-听
   

   Shallow Cloud Integration	Deep Cloud Integration
   Application is moved to the cloud on an as-is what is basis.	Application is changed during the migration.
   Move the application to the cloud with little or no change at all.	Migration is done to take advantage of cloud capabilities, and therefore change is necessary.听
   Does not affect the business results	Can help business results if it is done right. Automation and scalability can be enhanced by using cloud infrastructure.

   3. Establish KPIs for cloud migration- The key performance indicators should be established to understand the possible benefits and how to realize those benefits. With a clear goal in mind, the chance of successful migration is much better. For example, if you want to enhance the user experience, an important KPI can be Page Load Time, Lag, response time, etc. Similarly, if you want to increase sales, important KPIs can be cart additions, conversion rate, engagement rate, etc. Thus, if you can define the key indicators, goal attainment can be much easier.
   4. Determine the readiness of your organization- Once you are clear of the benefits and KPIs you would like to achieve, you should check if your legacy system is ready for cloud migration. If your organization does not have the relevant IT talent, you can hire a consultant to check cloud readiness. Most legacy systems are not cloud-friendly and use several in-house applications to fetch data. This can be a hurdle when moving to the cloud, as these applications will require higher online capacity.To ensure a smooth migration, follow the following steps: –
      1. List your applications.
      2. List the servers, hardware, and storage these applications are using.
      3. Collect the use case of these applications from respective application heads/users.
      4. Prepare dependency maps or flowcharts.
      5. Analyze听each application to prepare cloud migration plans and disentangle dependencies wherever possible.
         
         
   5. Choose a cloud service provider- The right service provider depends on your specific requirements, although some top organizations provide most of the features. Nevertheless, you should be willing to get a detailed understanding of the benefits each cloud service provider can give and then choose accordingly. Some of the factors to be considered are as follows: –
      1. Time to market- A good听enterprise cloud software听should allow听code to be written iteratively to enable automation. A quick response to market demand requires enterprises to have automated analytics cloud platforms. Automation allows the release of new capabilities faster, thus ensuring a shorter time to market. The听enterprise cloud software听should be automation-friendly.
      2. Innovation- A good cloud infrastructure should provide access to third-party applications to support innovation. Access to a third-party ecosystem ensures advanced technologies like data aggregation, quantum computing, facial recognition, and natural language processing.
      3. Lower security risk- Cloud infrastructure service providers can invest billions of dollars in cyber security. Thus, cyber security capabilities should be considered at the time of system selection for the cloud. Analytics cloud systems should be secure against cyber-attacks and other security threats.
      4. Scalability-听A good听enterprise cloud software听should allow scalability to respond to peak demand and uncertain business climate, especially in situations like Covid-19 disruptions. The cloud software should be scalable in seconds as the demand for usage increases. If the cloud is scalable, the business can be scaled without worrying about technology disruptions caused due to changing business environment. Competitiveness in the industry favors technologically scalable companies.
   6. Costs and Risks- Before selecting the correct听enterprise cloud software, you should list down all the costs and risks you are taking up. Remember, migrating to the cloud can be cost-intensive initially, depending on the size and data of the organization. You should first list down all the risks in the following categories: –
      1. Compliance risks
      2. Cybersecurity Risks
      3. Vendor Risk
      4. Cloud migration risk

A cost-benefit analysis should be done after the migration team quantifies all the risks.听

7. When finalizing your analytics cloud software, decide whether you desire Infrastructure as a Service(Iaas), or Platform as a Service(Paas), or Software as a Service(Saas). You should decide which one to use based on business requirements, business size, and scale. This decision should make use of business managers as well.

8. Prepare a cloud migration roadmap- After you have finalized the cloud service provider, you should prepare a migration roadmap with the help of the CIO, CTO, and cloud service provider. The migration can be one-time or incremental, depending on various factors. The advantage of incremental migration is that you can see some benefits accruing before you embark on more expenditure. If you can measure benefits, higher budget allocation is possible as the business gets involved in cloud migration.
9. Changing the DNA of the organization to become cloud-ready- If the cloud is integrated into the DNA of the organization, the culture of the organization will become aligned to cloud migration. This can get enhanced cooperation from all employees and thus a higher chance of adoption. This can be done as follows: –
   1. Change the thinking from projects to products- The IT Team should consider application functionality as a product that can solve a particular problem like Billing, Vendor Registration, Vendor Payments, etc. Thus, if the thinking of the IT team is product-based, cloud technologies can help automate various processes and thereby help the organization save time and money.
   2. Developer Experience- The technology development process should be redesigned end-to-end to make cloud-native experience possible for developers. This will help the organization to stay technologically relevant and solve technical problems in a cloud environment.
   3. Cloud should be abstract and automation-friendly- Complex dependencies should be avoided to ensure that the software is abstract and can be applied to various environments across different business segments. For example, the听marketing cloud software听should not reference the HR Cloud software. If the software is free of legacy dependencies, automation is possible, and the full benefit of cloud infrastructure can be realized.
10. Business Integration- The technology team should be integrated with the business team and should solve the problem from a business perspective. If the technology team understands the business, they are more likely to offer solutions that can help the business achieve better automation of various processes. Business engagement is essential in the following areas: –
    1. Budgeting- The budgeting is usually not from the technology team鈥檚 perspective. Budgeting is more likely to reflect business wants rather than technology wants. For example, the business requirement is more likely to be prioritized over automation spending. Automation spending can likely reduce technological costs in the future. Therefore, if possible, the business should be integrated at the budgeting level to ensure technological automation spending is not relegated.
    2. Collaboration-To extract full value from cloud systems, the business team should understand how to extract the value. Therefore, if there is a collaboration between the business and technology teams, the benefit of cloud migration is likely.
    3. Engineering Talent- Legacy companies have rigid hiring practices and getting a budget for cloud-specific IT talent is difficult. If the business is directly involved in cloud migration, specialized cloud technology and automation talent can be hired,听which can help the business succeed in the long term.

Business transformation on the cloud is becoming necessary and you should check out all the available service providers to help you in your journey to success. If you are looking for marketing cloud software听or general听enterprise cloud software, you can consider听. 51风流has an established reputation as an industry leader and can help your organization stay ahead.

The post How to Ensure Successful Business Transformation on Cloud? appeared first on 51风流India News Center.

Mumbai, January 20, 2022: Mahindra & Mahindra Ltd partners with 51风流to spearhead its digital transformation journey. 51风流will enable Mahindra & Mahindra to successfully modernize their technology landscape and enhance their overall operations by migrating 51风流to a secure managed cloud environment whilst moving to a microservices enabled open stack architecture enabled by using 51风流Business Technology Platform.

“Agility and business innovation is a priority in the changing industry dynamics and customer expectations,” says Mohit Kapoor, Group Chief Technology Officer – Mahindra & Mahindra Ltd. “ We believe that cloud is the change agent in digital transformation of the company by bringing in higher levels of intelligence and automation. 51风流on cloud adopts Business Transformation as a Service approach that aligns with our ambitious digital roadmap of reimagining customer journeys by transforming the core and using Data/AI for driving customer and employee experience.鈥�

Mahindra & Mahindra鈥檚 becomes a leader amongst Indian conglomerates to move their entire 51风流workload to a secure managed cloud environment to ensure a higher application-level SLA and reduce technical debt by transferring existing customizations to the cloud. Moving to the cloud will result in shortened time to market, faster bottom-line development, more business function productivity, and a decreased risk of non-compliance.

鈥淓xtending our support to our long-time customer, Mahindra & Mahindra is timely, as cloud migration is a growing trend in the rapidly changing business landscape鈥�, says Manish Prasad, Vice President 鈥� Metal, Mining, Miscellaneous & Automotive Industry 51风流India. 鈥�SAP’s industry centricity and processes will further drive substantial revolution for Mahindra & Mahindra’s cloud journey.鈥�

About Mahindra

Founded in 1945, the Mahindra Group is one of the largest and most admired multinational federation of companies with 260,000 employees in over 100 countries. It enjoys a leadership position in farm equipment, utility vehicles, information technology and financial services in India and is the world鈥檚 largest tractor company by volume. It has a strong presence in renewable energy, agriculture, logistics, hospitality and real estate.

The Mahindra Group has a clear focus on leading ESG globally, enabling rural prosperity and enhancing urban living, with a goal to drive positive change in the lives of communities and stakeholders to enable them to Rise.

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About SAP

SAP鈥檚 strategy is to help every business run as a sustainable intelligent enterprise. As a market leader in enterprise application software, we help companies of all sizes and in all industries run at their best: 87% of the world鈥檚 total global commerce touches an SAP庐 system. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers鈥� businesses into sustainable intelligent enterprises. 51风流helps give people and organizations deep business insight and fosters collaboration that helps them stay ahead of their competition. We simplify technology for companies so they can consume our software the way they want 鈥� without disruption. Our end-to-end suite of applications and services enables business and public customers across 25 industries globally to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, 51风流helps the world run better and improve people鈥檚 lives. For more information, visit www.sap.com.

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For further information please contact:

51风流India

Chaya Arora

Head 鈥� India Communications

chaya.arora@sap.com

The post Mahindra & Mahindra to Accelerate Cloud Transformation with SAP appeared first on 51风流India News Center.