A world led by digital transformation is a world that is driven by data. Every industry today depends highly on data gathering, storage, management and analysis- resulting in productive insights for strategic decision making and business growth. Today, data defines the success and failure of companies, its ability to disrupt or getting disrupted!
Brands are hence emphasizing greatly on transforming the way they collect, store or access data for cognitive insights into market and customers and delivering experience that truly meets the expectations of today's customers. The abundance of data with the rise of technological innovation and widespread availability of Big data has propelled brands to rethink their data infrastructure and capabilities. In this blog, we will discuss the top 6 trends in 2020 that is shaping the growth of data-ready enterprises.
1. Data-Ready Enterprises
The need to create flawless customer experiences, higher productivity and to achieve boosted business returns have pushed brands to adopt technologies that create products and services specifically designed to meet the needs of an evolving customer and their expectations. Brands today are leveraging modern innovative tools supported by artificial intelligence, machine learning and NLP and this demands them to build data infrastructure in a much more advanced and calibrated manner. Data infrastructure need to be so designed that they meet the requirements of modern applications unlike the traditional general- purpose applications. The need today is to create specialized architectures that are more agile, robust and swift with greater computing power, storage and networking capability.
2. Software Composability
Legacy data infrastructures are becoming unsustainable to meet the demands of data-intensive modern applications and data-driven environments due to their limited capabilities and uniform ratio for compute, storage and network bandwidth resources. This limits the capacity utilization of the data infrastructure as well as resource optimization. With Software Composability Infrastructure, companies are able to meet new levels of flexibility and performance predictability in their data centers where computing, network and storage are disaggregated into resource pools that are shared and treated as services. Since software composability does not need equipment reconfiguration or any physical involvement; servers can be provisioned in real-time. This will dramatically enhance server utilization and performance giving newer levels of flexibility and performance to data centers.
3. Fast Data
IT teams in every organization is faced with the challenge to tackle and manage the exponential growth of data. However, the most important factor with big data is that it is getting even faster with fast data. Organizations cannot compromise on the pace at which these logical are data gathered, stored, leveraged and analyzed for real-time analysis and prompt business decisions. Organizations need to adopt newer technologies that not just receives data but also interprets the large streams of incoming fast data by analyzing the live streams as soon as it is generated and enters the pipeline.
4. Automated Enterprise
Businesses are getting digital-first and led by new innovations around technology. Leveraging new technologies require businesses to accelerate their work process and reduce manual tasks and delays by leveraging new tools to automate the tasks. It helps them free up resources for strategic undertaking as IT teams support the business function by simplifying, automating and consolidating the hardware. Enterprises are increasingly deploying and implementing virtual machines and intelligent data management solutions to move cold data through automated policies for freeing up high performance data infrastructure and allowing IT teams more time to focus on business-critical tasks.
5. Smart Infrastructure
New tools and platforms are helping businesses track and measure the state of their hardware and systems through smart analytics that can leverage cloud to maximize the uptime and efficiencies. For e.g IT Departments in Companies can control their hard drives to make their systems hardware-aware, enabling automated testing for malfunction and misbehaving drives. It can help businesses find out if a drive had malfunctioned owing to hardware or system failure and with this built-in intelligence, they can reduce the number of returned drives and save time eventually.
6. End-to-End Programmability
The demand towards a programmable infrastructure is gaining an increased importance but it continues to be a challenge owing to the rate of change in technology. Multi cloud platforms, increasing numbers of SaaS providers, hyperconverged solutions and on-premise private cloud is growing steadily. A programmable infrastructure helps a business in ensuring that data infrastructure can quickly adapt to changing business needs for new applications and incoming data along with simplified governance enforcement and customization. End-to-end programmability thus offers improved performance and helps in automating infrastructure through applications via APIs.
These new trends create needs and challenges which traditional data infrastructure fails to meet. It also limits the ability of businesses to extract benefits of modern innovations - led by AI, data analytics and ML. These trends will continue to emerge and expand in several years to come. The future of data infrastructure will be built on the premise of reducing complexity and staying ahead of the time with quick adoption of new technologies for seamless data management and analysis.
It's time for brands to embark upon a strategy where policies, services and technologies are merged into a unified business unit to truly understand and exploit the real opportunities of modern digital age. If you are looking for a unified and simplified data infrastructure and management solutions, please reach us at firstname.lastname@example.org for any query subscribe to our blog to learn more for latest insights & updates.
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Brands today are leveraging modern innovative tools supported by artificial intelligence, machine learning and NLP and this demands them to build data infrastructure in a much more advanced and calibrated manner