Data Analytics & Interactive Dashboards
We enable investment managers to make superior and more confident investment decisions by automating the centralization of critical investment and operations data.
We then employ leading-edge, proprietary business intelligence, machine learning, and other data analytics and data visualization tools, to improve the quality, timeliness and visual presentation of their proprietary research and reports.
Centralization of Critical Investment & Operations Data
We realize that most successful investment managers are often inundated with data from numerous internal and external sources as well as in various formats.
We work with investment managers to help them better manage and analyze their data in a robust manner. This allows our clients to make more confident, timely investment decisions based on timely, accurate, and reliable data.
After working with a multitude of investment managers over the years, we have developed a proprietary two-step process to extract, clean, and aggregate data stored in numerous formats, and from numerous internal and external sources using our fast and efficient techniques.
Overview of Our Proprietary Bespoke Data Centralization Solution
We have developed a unique solution, which includes a proprietary process, internal documents and checklists, internal software, and tools. This approach ensures that the solution is executed successfully for each unique investment manager that we work with.
Step 1: Inventory of Current Data, Sources & Utilization Across the Investment Firm
We start by meeting with your internal team. During this confidential session, which typically takes about two hours:
We discuss and understand your current data strategy
Take an inventory of the current data assets, sources (both structured and unstructured data), and what systems, processes and reports use the available data.
In addition, we also take inventory of the technology and software infrastructure being utilized to manage and analyze data.
Once the initial session is complete, we typically take about 2-3 weeks to work with your internal teams and complete a comprehensive assessment of your current data strategy, including your data assets, sources and the usage of your data.
Once the assessment is complete, we set up a second meeting with your team to present the results of our findings. In this meeting, we recommend and explain the best possible technical solution for extracting, cleaning, normalizing, and aggregating your fund data.
This solution is customized to your firm’s investment process, operational setups and infrastructure, as well as reflecting your future growth plans.
Step 2 – Aggregation, Centralization & Management of Investment & Operations Data
In this step, we work with your team to extract data from various internal sources including (1) Microsoft Excel workbooks, (2) PDF files, (3) CSV files, (4) XML files, (5) Emails (including attachments), (6) FTP servers, (7) APIs, and other data sources.
Data extracted from all of these sources is then aggregated into a central data warehouse that is
designed to store this data in a highly structured and relational manner.
We import and backfill the current data into this new relational database, which is then utilized to generate various reports and analysis.
This step typically takes about 4-6 weeks to implement.
Data Analytics & Interactive Dashboards
We work with investment managers to help them better analyze their data. This enables our clients to make more confident, profitable investment decisions based on timely, and reliable data analysis that is presented using an interactive dashboard that is visually attractive and easy to understand.
After working with a multitude of investment managers over the years, we have developed both the domain knowledge and numerous proprietary software, tools and APIs to efficiently deploy the recommended solution. This unique combination enables our clients to gain access to timely, accurate, and reliable data analytics via visually attractive, interactive dashboards.
Data Visualization Software & Tools
Microsoft Power BI
Python libraries including – NumPy, SciPy, Pandas, Statsmodels, Quandl, Zipline, QuantLib, Matplotlibm, etc.
R libraries including – Quantmod, Portfolio Analytics, Performance Analytics, DerivMkts, etc.
Proprietary tools built on C, C#, R & Python programming languages.