DAX Optimizer Verified Customer Reviews (2026)

Budgyt is budgeting and forecasting software created by a former CFO who was tired of Excel breaking at the worst possible moments. We serve finance teams at growing organizations managing multiple departments, locations, or grants. 350+ organizations and 4,000+ users have made the switch. The core features solve what breaks in Excel. Import your chart of accounts and actuals directly from your accounting system via API. Click any variance to drill down to vendor-level detail with complete audit trails. Run rolling reforecasts monthly without rebuilding everything. Built-in payroll allocation, automated accruals, balance sheet and cash flow forecasting. Dynamic driver formulas that work like Excel but never break. Unbreakable formulas you manage without syntax. Unlimited team collaboration with approvals and activity tracking. Single source of truth for your entire organization. Budgyt replaces Excel without the learning curve. No broken formulas. No version chaos. No board meeting panic. Works like Excel. Except it actually works. Up and running in hours via API, not months of consulting.

Ensuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.

Melder represents a cutting-edge Excel add-in that harnesses the power of AI to incorporate generative intelligence directly into spreadsheets, enabling users to easily upload various documents and web materials while making use of intuitive AI-driven formulas right within Excel. This tool allows for the straightforward insertion of PDFs and other document types into spreadsheet cells, where users can apply formulas to summarize, extract, classify, and analyze the inserted content, complete with clickable citations linking back to the original sources for verification purposes. Additionally, a specialized chat assistant positioned in the sidebar provides users with the ability to ask questions or develop workflows within their workbooks, significantly boosting productivity levels. Melder excels at automating repetitive tasks, such as deriving crucial insights from data rooms, reviewing contracts by pinpointing key terms, streamlining market research via data collection from competitor websites, and synthesizing transcripts from interviews or calls, all achievable through Excel formulas without the need to toggle between different applications. The integration of Melder not only enhances the overall functionality of Excel but also empowers users to manage their data more efficiently, ultimately leading to considerable time savings and reduced effort in their workflows. By transforming the Excel experience, Melder equips users to tackle complex tasks with ease and precision.