Big data is the cornerstone of digital transformation and artificial intelligence . For the future development trend of big data . As 2023 approaches, many professionals have expressed their views and attitudes towards the prospects of big data.
Fivetran Product Owner Alexander Lovell believes next year will be a critical year for the big data space: "Data teams will either grow or shut down in 2023. Although the quality of returns from big data applications varies widely across enterprises, companies are continuing to invest. With widespread disruption in the economy, now is the time for data teams to clear the fog by providing valuable insights as the market continues to change. Executing on intuition is too unreliable. The best data teams will grow and become more important, and the teams that are not able to produce actionable insights will face greater pressure,” said Mike, CEO and co-founder of
Datometry. Waas said that by 2023, SQL will rise again. The NoSQL community began to reflect on the value of SQL, acknowledging that enterprises needed standards and the simplicity of SQL as a general-purpose and powerful query language. Virtually every NoSQL database still alive is currently adding SQL or SQL interfaces to their systems to attract enterprises. Nearly every data management system that wants to be successful in an enterprise in 2023 will try to leverage SQL, which looks like a suitable database. "
Data has also gone through phases in history, from centralization to distribution to centralization, and now distribution is prevalent again. Angel Viña, CEO and founder of Denodo, said that we are currently in the distributed phase and are unlikely to return to the past, so new methods are needed to deal with it, including Data Fabric or Data Grid. Mesh).
"While there are inherent differences between the two, Data Grid is a set of composable data management technologies and Data Grid is a process-oriented approach for distributed teams to manage enterprise data. Both can play a key role in enterprise-wide data access, integration, management and delivery, and if the right data infrastructure is in place, adoption of both architectural approaches is expected to increase rapidly within mid- to large-sized enterprises in 2023. "
You've heard about modern data stacks. But in 2023, you'll be hearing a lot more about postmodern data stacks," said Chris Lubasch, CDO at Snowplow. "It's been a year of rapid discussion around modern data stacks." Despite the challenging economic climate, many new vendors have emerged, with major vendors such as Snowflake and Databricks continuing to take over many technology components. At the same time, voices are emerging that question modern data stacks, as their approach often results in the prohibitive cost of many tools, not to mention the complexity of bringing them together. The discussion around the “postmodern data stack” (as one of many terms) has begun, and we are all eager to see where this will lead us in the coming years. ”
As the founder of object storage provider Cleversafe (acquired by IBM for $1.3 billion in 2015), Chris Gladwin predicts that 2023 will be the year when ultra-large-scale data becomes mainstream.
Data-intensive enterprises are moving beyond big data and into the exponentially larger world of hyperscale data, which will require a re-evaluation of data infrastructure. By 2023, data warehouse vendors will develop new ways to build and scale systems and services.
It’s not just the data that technicians have to plan for volumes, as well as emerging data sets and pending workloads. Some leading IT organizations are now processing data sets containing billions and trillions of records. By 2023, we could even see data sets with billions of rows in data-intensive industries such as advertising, telecommunications, and geospatial. Hyperscale data sets will become increasingly common as organizations leverage increasing amounts of near-real-time data from operations, customers, and mobile devices. ”
Immuta CEO and Co-Founder Matt Carroll said that 2023 will see the rise of data processing agreements (DPAs).“By 2023, we will see DPA become a standard element of SaaS contracts and data sharing negotiations. How organizations approach these contracts will fundamentally change how they build data infrastructure and define the business value of data. Therefore, data leaders are most interested in fully embracing DP in 2023 and beyond A. These lengthy documents will be complex and the involvement of DPA’s digital and legal teams will make them easier to understand and implement.
“By 2023, as data sharing continues to grow and data and IT teams are forced to keep up, data exchange will become the new standard. As organizations produce modern data stacks, scale and volume will explode. It will no longer be feasible to make copies of datasets before sharing them. By 2023, enterprises will flock to established platforms like Snowflake’s Data Exchange and Databricks’ Delta Sharing Protocol to make it easier to securely share and monetize circulating data.
And in the opinion of Dhruba Borthakur, co-founder and CTO of Rockset and founding engineer of RocksDB, 2023 will be the year of data applications.
"Over the past 10 years, we have seen the rise of web applications and mobile applications, but 2023 is the year of data applications." Reliable, high-performance data applications will prove to be a critical tool for success as enterprises seek new solutions to improve customer-facing applications and internal business operations. On-demand data apps like Uber, Lyft, and Doordash are available at our fingertips. Powered by a real-time analytics foundation, we will see increasing pressure for data applications to be not only real-time, but also fail-safe. "
There are probably a lot of things on your New Year's shopping list. But Tamr chief product officer Anthony Deighton is hoping for one thing this year: clean data.
"'Dirty' data is incorrect, incomplete, inconsistent, outdated, duplicate data that can kill your business and is a common problem. Avoid confusion and frustration. Customer Mastery creates a unified, accurate and rich view of customer data across systems and sources, along with unique identifiers that enable consistent tracking of customers. Mastering customer data at scale provides sales, marketing, and customer experience teams with an effective way to accelerate data-driven sales. It can also provide customers with insights to gain a competitive advantage.
According to Andi Gutmans, vice president and general manager of Google Cloud Database, the barrier between transactional and analytical workloads will start to disappear in 2023.
"Traditionally, data architecture has separated these workloads because each workload requires a fit-for-purpose database, with interactive databases optimized for fast reads and writes and analytical databases optimized for aggregating large data sets," Gutmans said. As cloud-based data architectures evolve that leverage highly scalable, disaggregated compute and storage over high-performance networks, we predict there will be new database architectures that allow transactional and analytical workloads to be conducted within a single system without requiring applications to compromise workload demands.
There are many people who are not bullish on big data. But Christian Buckner, senior vice president of data analytics and IoT at Altair, said he doesn't believe the hype.
"Big data is not dead yet," he said. "Providers will try to get ahead of the trend, and we will see a lot of people start to preach that 'big data is dead.' Instead, many organizations are turning to 'smart data' to gain deeper insights. But big data will continue to play an important role in business operations. The key is to ensure you have easy-to-use self-service tools to clean, validate and prepare your data, which can then be plugged into data analysis models to get valuable results and intelligent decisions. Companies that turn big data into smart data will benefit from new ways of thinking about data. "
When it comes to data democratization, that will come in the form of Python, according to Torsten Grabs, director of product management at Snowflake.
"By 2023, Python will be the primary medium for democratizing access to data and insights for everyone across the organization. Python will become more enterprise-friendly as the runtime infrastructure around it becomes simpler, more straightforward, and includes more security. At the same time, generating Python results will become even more streamlined." ization, the code will be wrapped in a meaningful user experience so that non-IT users such as corporate marketing teams can easily consume and understand it. We will see Python having the same or greater potential to transform data democratization than the advent of self-service business intelligence tools 15 to 20 years ago."
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