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A few days after the Gartner shares decreased by 50 % regarding warnings to slow the purchases of institution technology, Snowfall Anti -pioneer was handed over. Institutions do not retract data infrastructure. They multiply.
The cloud data platform company has registered 32 % growth on an annual basis in product revenues for the second quarter of the fiscal year, accelerated from the previous quarter and added 533 new customers. More for the leaders of institution technology, the AI’s work burdens now affect approximately 50 % of the new customer victories and the strength of 25 % of all cases of use scattered across the Snowflake platform.
“Our basic business analyzes are still strong,” Sridehar Ramasuami, CEO of Snouflake, said during the profit call. But he stressed something more important: “This data updating journey is more important than before because they realize that Amnesty International transforms the work of the work on how they interact with their clients depend in a critical way to obtain their data in a place ready for the reality of intelligence.”
The infrastructure of artificial intelligence data is necessary
This dynamic reveals the reason for the emergence of the Foundation’s data, isolated from the budget budget restrictions. Contrary to the purchase of the estimated programs that can be postponed, the data infrastructure has become an important important for artificial intelligence initiatives.
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Snowflake shows that companies continue to invest in data, analyzes and AI, and improve efficiency as a way to achieve profit goals in the face of economic opposite winds, “Kevin Petrie, Research in Bless usTell Venturebeat. “We find that most companies prefer to work with the current sellers during the experience and spread of artificial intelligence.”
Snowflake’s technical standards confirm this urgency. The company launched 250 new capabilities for general availability in only six months. New features extend four main areas: analyzes, Data engineeringAI, applications and cooperation. More than 6100 account is now used by Snowflake Ai Weekly capabilities, which represents the adoption of rapid institutions for the burdens of AI production.
The new company Snowfish intelligence The basic system provides natural language information via organized and unorganized data while directly operating smart agents on institutions data groups. The first trap, such as Cambia Health Solutions, has published it to analyze huge amounts of longitudinal health care. Duck Creek Technologies uses sales, sales and human resources.
Technical architecture growth that drives growth
Several technical developments explain the reason for accelerating institutions, instead of slowing down, their investments on data platforms.
Unified from artificial intelligence and analyzes: The new snowflake AI SQL crust It brings artificial intelligence models directly in SQL Information. This removes data movement and enables the acting analysis in the actual time. The architectural approach addresses a major concern about artificial intelligence applications: data governance and security.
Performance improvementThe company’s Gen 2 warehouse offers up to 2x faster with resource improving automatically. This addresses the cost concerns that may slow down the adoption.
Immigration acceleration: Improved tools for the transfer of local old systems to cloud platforms that reduce the timelines for implementation. This makes modernization projects more acceptable even during unconfirmed economic periods.
Integration of open standards: to support Apache iceberg The new Connect Connect for Apache Spark cancels the seller’s lock fears that can delay the decisions of institutions.
“Many companies already have snowflake data warehouses, so they have a natural tendency to use their tools for artificial intelligence initiatives,” Petri pointed out. “Snowflake’s power in data warehouses also gives a leg in artificial intelligence initiatives because organized data remains the preferred inputs of artificial intelligence models/ml.”
Context: Data for appreciated technical spending
The contradiction with the recent market signals is Stark. Gartner’s warning against slowing the purchases of institution technology, along with the research of the Massachusetts Institute of Technology, indicating the conditions of the potential artificial intelligence bubble, has disturbed investors on the demand for institution technology. However, Snowflake’s results indicate a branch of institutions spending.
Noel YuhanaVice President and main analyst in Forster, believes that this verification is valid for a wider direction. “Snowflake’s results reflect a wider direction: the data market is accelerating, driven by increasing demand for integrated, reliable and ready -made data from artificial intelligence,” Yuhanna told Venturebeat. “With organizations race to run artificial intelligence, they realize that raw or horrific data is not enough. Data must be trial, high -quality, and can be widely accessible.”
Market flexibility despite the doubts of artificial intelligence
Industry analyst Sanjif Mohan It is believed that this flexibility will continue despite the potential corrections in the artificial intelligence market.
Mohan told Venturebeat: “I am pleased to see the outstanding financial performance of Snowflake and not surprised at all.” “It confirms how institutions invest in ensuring that their data are accurate, relevant and unified in one system.”
Mohan refused to fears that investment fatigue of artificial intelligence will affect data platforms.
“Yes, Gartner’s shares decreased as customers tightened appreciation spending,” he said. “But even if the growth of Ai Company, I think Snowflake, Databrics, Google Cloud, Hyperscalers and other huge sellers will continue to flourish.”
The area of the basic shift in how institutions are presented to the infrastructure of data.
“If Gen AI taught us anything, this is: without reliable data, there is no trench.”
Strategic effects of institution leaders
For technological decision makers, SNOWFLAKE performs many decisive trends.
Data infrastructure as a competitive trenchInstitutions that postpone the risk of data update abandoning competitors who are already publishing the workflow work that works on behalf.
Integration on replacementInstead of updating wholesale technology, successful companies combine artificial intelligence capabilities into current data platforms. This approach reduces risks and speeds up value.
The first strategy of artificial intelligence governance: The focus on “AI’s Ready Data” indicates that priority companies to manage data are in a better position for the success of artificial intelligence. This means governed, high -quality data sets, which can be accessed instead of raw or horrific information.
The difference between fears of general technological spending and the growth of the data platform investment creates both risks and opportunities for institution leaders. The broader lesson is clear. While some technological investments may face scrutiny of unconfirmed economic times, the infrastructure of the data has exceeded the estimated spending to become the basic ability of the institution. Companies that recognize this transformation and investment will be placed according to this to take advantage of the opportunities for artificial intelligence, regardless of the wider market conditions.
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