The only thing you own on the cloud is your data.
Innovation & dynamic business agility with cloud:
Business resilience and agility are more important than ever in these challenging times. To succeed in the digital era, organizations must be able to leverage their enterprise data and automate operations. The need for data is skyrocketing, yet very few businesses are putting their data to work to gain a competitive advantage.
By the end of 2022, the cloud market is most likely to reach the predicted $495 billion mark. The size of the international cloud market is $445.3 billion with a CAGR of 16.3%, expected to reach USD $947.3 billion by 2026.
To become data-driven, organizations must leverage cloud as a catalyst. To drive game-changing insights from data, businesses should develop a “data on cloud” strategy tied to business outcomes. Organizations must transition from their outdated systems and processes with more advanced, adaptable, and scalable data architecture on the cloud. This can stimulate business outcomes by reducing the processing time (often by more than 50% as we have seen with some of our customers), and driving faster and accurate decisions.
Organizations require a data intelligence engine that will maximize the potential of their data, guarantee its reliability, and provide data consumers with the appropriate data at the appropriate time.
Getting to the Cloud:
Enterprises that have a solid cloud strategy will empower employees with self-serve analytics, act rapidly to addressing new business demands, and quickly transition machine learning (ML) experiments to productionalized assets. Unfortunately, a lot of businesses see cloud as mainly an IT project.
Without the involvement of other business units, data lakes that build more information quickly turn into useless data swamps. A lack of governance, old operating models, outdated skills and cultures, and concerns with data quality are the key challenges they encounter, which might restrict the advantages of the cloud.
Data on Cloud:
A thoughtful and flexible strategy is necessary for successful cloud migration. Businesses can instantly democratise access to data, make data-driven choices more readily, cut operational expenses, and accelerate the transition from experimentation to innovation by storing and processing data on the cloud.
To succeed in this new environment, organisations must develop a cutting-edge intelligent data organisation focused on four essential data management journeys:
Analytics, AI & Data Warehouse, and Lake
Application Integration & Hyper-automation
Master Data Management & 360 Applications
Data Governance & Privacy
The need for Intelligent Cloud Solutions:
In the modern world, all new apps must be cloud-based and deployable from any location at a global scale and reach. Organizations must adapt their business processes quickly to increase time to market, improve customer experience, drive digital commerce, streamline the supply chain, and more. An organization’s ability to quickly combine the best technology infrastructure with a best-of-breed data management platform is key to its sustainable long-term success.
Because of the complexity of the data landscape, heterogeneous infrastructure, legacy applications, and administrative processes, it is necessary to create a baseline for transformation to identify any potential gaps and to design a data architecture that is future-proof while still protecting and securing data. Data lakes or data lake houses alone cannot solve the efficiency problem. This is because most of the data generated today are unstructured, creating scale and affordability challenges. Intelligent cloud solutions will focus on utilizing unstructured data and lower the cost of data storage. Data management and AI will need to take the lead in innovation due to the unfathomable size at which data could amass in this decade.
Cloud Business Transformation through Data Strategy:
Everyone is aware of the capabilities and power of the cloud. Cloud-based approach is particularly useful while managing, comprehending, and gaining insights from extremely huge volumes of unstructured data. Cloud also offers elasticity and the ability to provide processing power and storage on demand. However, there are ongoing challenges such as:
Informatica Intelligent Cloud Services:
Most businesses today are modernizing their analytics in the cloud. They need cloud native data management to fully reap the benefits of cloud data warehouses, data lakes, and lake houses. They require cloud-native, intelligent, automated meta data management, data integration, cataloging, data quality, and master data management systems.
All of this adds up to informatica Intelligent Cloud Services, a new generation of iPaaS that support all cloud ecosystems, including Google Cloud Platform, Amazon Web Services, Microsoft Azure, Snowflake, and Databricks. It is built to address constantly expanding line of cloud data management products. Informatica has designed it’s cloud-native data management to adapt to big data platforms, such as Cloudera, fit for purpose-specific data warehouses, platforms for data science, and applications, and cloud platforms, such as SAP, Oracle, and IBM.
Informatica Intelligent Data Management Cloud:
For data management on a single platform at scale and in the cloud, the Informatica’s Intelligent Data Management Cloud™(IDMC) offers strong AI and more than 200 intelligent cloud services. It enables you to link the appropriate data securely and easily.
You can integrate data anywhere on any platform with IDMC. Generating the high-quality data and insights required to drive genuine digital change, and IDMC provides the scale you want with over 32 trillion transactions each month. Additionally, you can catalogue, ingest, integrate, prepare, clean, master, and share all your data, wherever it is, and process it anyway you like with the help of more than 200 cloud-native intelligent data services. Providing trusted, democratised information with a 360-degree picture view of your company’s operations on a foundation of governance, the only platform you’ll ever need for data management at scale and in the cloud.
The cloud-native service from Informatica uses automation to address the problems of data fragmentation and complexity, allowing businesses to concentrate on innovation driven by reliable data rather than speculation. IDMC handles all your data management issues whether they are in an on-premises, SaaS, or hybrid data estate. Informatica’s modular, cloud-native, metadata-driven platform leverages AI to quickly find and incorporate high-value data while safeguarding, managing, and controlling it.
All your company operations, departmental apps, procedures, and users are connected by your data. Every employee in your company may provide previously unheard-of value for your clients, partners, suppliers, and stakeholders thanks to data. There are always quality issues and gaps in the data. Due to the quick transition to digital, data is being produced at an uncontrollable rate. Modernizing now entails more than simply a straightforward lift-and-shift to the cloud. To manage the enormous volume and variety of data pouring in from numerous sources, you must rely on SaaS and PaaS solutions. Additionally, there is not enough manpower to handle this data growing at an exponential rate. AI is required to support human decision-making and corporate operations.
Over the following five years, we anticipate businesses to transform into intelligent data firms that use data as their platform, which will foster innovation. Only when your data is widely accessible and easily discoverable can you use it as your advantage. It must be managed, protected, and shareable, and everyone must be able to rely on it to innovate and do business.
Customers of Informatica all over the world are using data as their platform to produce substantial business results that position them as leaders in their industries. These customers have overcome the data islands that have grown through time and the inability to fully realise the benefits of a single, precise view of the business by using data as a platform.
Stay tuned to Part 2 of the blog series that focuses on the Informatica difference.