According to study results by Fivetran, 86% of companies struggle to trust AI to make all business decisions without human participation. In contrast, 90% of enterprises rely on manual data procedures. The companion paper, "Achieving AI: A Study of AI Opportunities and Obstacles," explains the problems businesses confront in today's AI ecosystem. The paper investigates how, even though 87% of businesses identify AI as the future of business and aim to expand their investment in it, a lack of trust in machine-led decision-making is a significant obstacle caused by technical challenges and a lack of education. Only 14% of respondents believe their companies are "advanced" in AI maturity.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Even as decision-makers and CXOs remain bullish on AI's potential, enterprises are struggling to make the most of it at the ground level. Case in point: a new report from data integration giant Fivetran that says 71% of companies find it difficult to access all the data needed to run AI programs, workloads and models. Working with Vanson Bourne, the company surveyed 550 IT and data science professionals in multiple countries and found gaps in data movement and access across their organizations.

From Fivetran's founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We're proud that more organizations continue to leverage our technology every day to become truly data-driven. Fivetran is looking for an Engineering Manager to join the Databases engineering leadership team. You will be working closely with engineers and product managers to build the future of the Fivetran Data Platform.

From Fivetran's founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We're proud that more organizations continue to leverage our technology every day to become truly data-driven. The Professional Services team at Fivetran is growing and you have the opportunity to join a function that is building from the ground up. The approaches, methodologies, working practices and team culture that we put in place now will be the template for what is to come, so if you are excited about having a hand in steering the approach of a critical function within the organisation then this may be the role for you!

Databricks, the Data and AI company and pioneer of the data lakehouse architecture, today announced Databricks Partner Connect, a one-stop portal for customers to quickly discover a broad set of validated data, analytics, and AI tools and easily integrate them with their Databricks lakehouse across multiple cloud providers. Integrations with Databricks partners Fivetran, Labelbox, Microsoft Power BI, Prophecy, Rivery, and Tableau are initially available to customers, with Airbyte, Blitzz, dbt Labs, and many more to come in the months ahead. Enterprises want to drive complexity out of their data infrastructure and adopt more open technologies to take better advantage of analytics and AI. The data lakehouse enabled by Databricks has put thousands of customers on this path, collectively processing multiple exabytes of data a day on a single platform for analytics and AI workloads. But, the data ecosystem is vast, and no one vendor can accomplish everything.

Fivetran took a big step into the world of enterprise data integration today when it announced an Andreessen Horowitz-led $565 million round of financing and plans to acquire change data capture (CDC) vendor HVR for $700 million. The move positions the up-and-coming ETL company to further access exabytes of data stored in on-prem databases and ERP systems on behalf of its customers. The Series C round and acquisition position Fivetran to be at the forefront of the next generation of data integration and extract, transform, and load (ETL) capabilities. The nine-year-old, Oakland, California company has made its mark by simplifying the process of setting up pipelines that extract data from source systems–primarily SaaS applications running on clouds–and load it into cloud-based data warehouses. Today's news will help to expand Fivetran's footprint with on-prem systems, including the ERP applications at the heart of established enterprises.

Data analytics practices are plagued with inefficiencies, according to a new report from automated data integration provider Fivetran. Polling circa 500 data professionals, the firm uncovered "surprising" information surrounding how data analysts spend their working days and the challenges they face. According to Fivetran, most data analysts spend less than half of the day actually analysing data. Much of the rest of the day is wasted as a result of various bottlenecks. For example, more than 60 percent reported wasting time waiting for engineering resources, multiple times a month.

Business use of AI grew 270% over the past four years, according to Gartner, while Deloitte says 62% of respondents to its corporate October 2018 report deployed some form of AI. That's up 53% from a year ago, but what we've learned is that adoption doesn't equal success, and success is an evolving model in this phase of our digital revolution. Unfortunately, roughly 25% of companies have seen half of their AI projects fail. Failure, in heavily technical deployments, like AI projects, is incredibly expensive when data scientist and other team time, technical cost of computation, and resources wasted is accounted for. Statistics like these have generated tremendous buzz around the end results: success or failure, but we've reached a pivot point where we must widen our lens and shift our attention.