Cube semantic layer eases data access from Power BI, Excel

[Pelican Press 0]

This is the hidden content, please

• Sign In
• or
• Sign Up

Cube semantic layer eases data access from Power ***, Excel

Cube unveiled an expanded partnership with

This is the hidden content, please

• Sign In
• or
• Sign Up

, launching new integrations between its semantic layer and both Power *** and Excel, enabling joint customers to better access data for analysis.

Based in San Francisco, Cube is a 2019 startup whose Cube Cloud platform is a semantic layer designed to enable users to eliminate isolated data, establish consistent models and governance, simplify access and exploration, discover data for reuse and easily integrate with APIs.

Data Analysis Expressions (DAX) API for Power *** integrates Cube’s semantic layer with Power *** so that joint customers can access live data in cloud data warehouses directly from Power *** using DAX, Power ***’s native query language.

Cube Cloud for Excel Add-in, meanwhile, uses Cube’s Multidimensional Expressions (MDX) API to connect governed data with Excel so users can update spreadsheets with a single click to analyze current data.

Accessing live data in data warehouses has been a struggle for many Power *** users, according to Donald Farmer, founder and principal of TreeHive Strategy. As a result, Cube’s new integration with Power ***, launched on Feb. 18, and its semantic layer is a significant addition for joint Cube and

This is the hidden content, please

• Sign In
• or
• Sign Up

customers. 

“The ability to query cloud data warehouses with DAX really is a breakthrough for teams who have struggled to make Power *** work with their preferred data warehouse platforms,” Farmer said, noting that even using Power *** with

This is the hidden content, please

• Sign In
• or
• Sign Up

’s own Fabric platform has been a struggle for data architects and engineers.

Regarding the integration between Cube’s semantic layer and Excel, Farmer added that it also is significant because it simplifies connections between Excel and cloud data storage platforms.

“The Excel connectivity is also an excellent addition,” he said.

Cube and

This is the hidden content, please

• Sign In
• or
• Sign Up

first partnered in March 2024.

New capabilities

Data architects and engineers have long been able to connect Power *** and Excel directly to data warehouses such as Azure or third-party platforms, including Databricks and Snowflake.

Such direct connections, however, don’t always work smoothly.

MDX was developed by

This is the hidden content, please

• Sign In
• or
• Sign Up

in the late 1990s to connect analytics tools with multi-dimensional online application processing (OLAP) cubes. DAX was developed later by

This is the hidden content, please

• Sign In
• or
• Sign Up

as an intended improvement and became the query language for Power ***.

Neither, however, is the current industry standard. Instead,

This is the hidden content, please

• Sign In
• or
• Sign Up

the query language for most analytics and data warehouse platforms.

Before Cube’s new integrations, Power *** and Excel users had to either copy and move data from data warehouses via import mode or MDX and DAX needed to be translated to SQL in

This is the hidden content, please

• Sign In
• or
• Sign Up

’s DirectQuery mode. Copying and moving data can be labor intensive. At the same time, translations from

This is the hidden content, please

• Sign In
• or
• Sign Up

’s query languages to SQL are not always seamless, which leads to lack of performance, according to Artyom Keydunov, Cube’s founder and CEO.

The integrations between Cube’s semantic layer and

This is the hidden content, please

• Sign In
• or
• Sign Up

’s analytics platforms are intended to

This is the hidden content, please

• Sign In
• or
• Sign Up

.

“The SQL generated is frequently unoptimized and performs poorly,” Keydunov said. “Our aim with the [the integrations] is to improve this performance.”

Because the integrations improve query performance between Power *** and Excel and cloud data warehouses, they address major trends, according to Kevin Petrie, an analyst at BARC U.S.

One is the sustained popularity of spreadsheets. Another is that

This is the hidden content, please

• Sign In
• or
• Sign Up

despite the efforts of cloud data platforms to help organizations consolidate. As a result, the integrations are noteworthy.

“This announcement gives companies a useful method of analyzing data,” Petrie said. “Analysts and data teams of all types need to access distributed data wherever it resides in order to drive decisions and support increasingly advanced models.” 

Like Keydunov, Farmer noted that direct connections between

This is the hidden content, please

• Sign In
• or
• Sign Up

’s analytics platforms and data warehouses often produce poor results. In addition, for those choosing to use DirectQuery, costs can add up, he continued.

Cube’s semantic layer enables users to cache data, which results in more efficient access from Power *** and Excel. And it enables such access via DAX and MDX.

“By enabling connectivity with both these standards, Cube has created a modern OLAP solution which is a real breakthrough in engineering for them,” Farmer said.

Regarding the impetus for integrating Cube’s semantic layer with Power *** and Excel, customer feedback was a significant factor, according to Keydunov.

Power *** is perhaps the most widely used business intelligence platform, with over 12 million users. Excel, meanwhile, remains the most popular tool for business analysis, with over 750 million users.

“The continued investments in new

This is the hidden content, please

• Sign In
• or
• Sign Up

integrations are a direct response to enterprise customer demand for these capabilities,” Keydunov said.

Future plans

In addition to its partnership with

This is the hidden content, please

• Sign In
• or
• Sign Up

, Cube is a partner with AWS,

This is the hidden content, please

• Sign In
• or
• Sign Up

Cloud, Databricks and Snowflake.

However, despite integrations with prominent data platform vendors, Cube’s semantic layer platform is a relative newcomer compared to others providing similar capabilities, such as AtScale, GoodData, Looker and MicroStrategy. In addition, its total funding of $46.7 million, including $25 million in 2024, is far less than that of other competitors, such as DBT Labs.

To compete, one of Cube’s goals is to continue modernizing OLAP, according to Keydunov. Another is to emerge as a catalyst for AI adoption by enabling customers to turn raw cloud data into AI-ready data.

“With well-defined semantic modeling, it becomes possible to deliver consistent, reliable, and trustworthy AI outputs and autonomous actions,” Keydunov said.

That focus on supporting AI platforms is wise, according to Petrie.

Universal semantic layers are a valuable way to unify access to distributed data, he noted. Migrating data, data sovereignty requirements and security risks often prevent organizations from consolidating data in one location. Semantic layers help address that sprawl.

Access to data, meanwhile, is critical for AI development. Cube now supports platforms such as the LangChain framework. But there are opportunities to integrate with others, according to Petrie.

“I would recommend they consider extending their support to include other AI/ML platforms such as Dataiku and Domino Data Lab,” he said. “Data scientists need easy access to structured data as they train advanced models and put them into production.”

Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.

This is the hidden content, please

• Sign In
• or
• Sign Up

#Cube #semantic #layer #eases #data #access #Power #Excel

This is the hidden content, please

• Sign In
• or
• Sign Up

This is the hidden content, please

• Sign In
• or
• Sign Up