Big Data Analytics
A simple, wizard-driven approach for optimizing certain workloads from a data warehouse and Cloudera Enterprise.
Data Warehouse & Data Marts
From Data Modeling to Reverse Engineering: an intuitive and complete design studio for your analytics architect team.
Business Intelligence & Discovery Tools
Embedded within your analytics front-end and dynamic documentation of all your BI reports.
The Google MapsTM
of your data
Self Service Business Intelligence is an important and powerful idea but has some disadvantages, too. Data models are easy… just when looking at demos. Real life is much more difficult. And this means that just looking at names of meta data, or at data itself, doesn’t help when it comes to aggregate numbers and extract meaning from it. What if we have a navigator? A Google Maps of your data model that helps business users understand where they are in their data structure? To see, like Map View, what a KPI means and how it is related with another one? This stuff has a name: top down exploration with indyco Explorer.
When it comes to reading dashboards, reports and KPIs in a real life environment, it is so easy to have many doubts: What does this term mean? How is this data calculated? Where does this data come from? Using indyco Explorer as a companion to your BI front end, you can leverage a state-of-the-art user experience that can make any user feels at home. Easily get the highest value from your data by exploring your business model through a graphical map that will stop you from ever losing your way. Validate and share your requirements, accessing a glossary of metrics and analysis perspectives shared by all business departments.
There are situations in which you really don’t know where to start when you want to analyze your data in order to get answers to your business questions. How do you approach the internet when you have questions? You search for it with Google. That’s why we have built in to indyco Explorer a powerful search capability. Our search autocomplete user interface feature provides you results as you type so you can quickly access the information you were looking for in any area they appear.
If you have a Data Warehouse, you surely already have a front end where your data is visualised. And your front end surely has an online help feature. But what about the help for your data model? indyco Explorer allows you to define custom views. You can navigate your model once and for all and reach the part of your data model that’s the representation of a specific report. Then you can save this custom view and store it for further use, such as the online help of your BI Dashboard. Nice, huh?
Data Models in real life are pretty intricate: difficult metrics coupled with various dimensions have an intrinsic complexity. A well-designed user interface is the only way to make difficult topics simple. That’s why indyco Explorer has been designed with user experience experts and offer different visualisation options: a graphical and a tabular one to meet every user’s expectations.
Make sense of your business through conceptual modeling
Many companies already have Data Warehouses in house. They can be Enterprise Data Warehouses or tactical Data Marts. They are often the result of years of sweat and tears, but sometimes you don’t know exactly how they are, or they are poorly documented. Reverse Engineering your Data Warehouse is a way to exploit the assets you have and speed up the design process. Worried about the status of your Data Warehouse? Assess it anyway by importing the data structure and converting it to the conceptual model.
Multidimensional modeling is a key issue in Data Warehouse design. While practitioners often face this task by directly designing star or snowflake schemas, distinguishing between a phase of conceptual design (that delivers an implementation-independent and expressive representation of multidimensional cubes) and one of logical design (that creates a corresponding logical schema on the chosen platform) brings doubtless advantages to both designers and end-users. Using the DFM (Dimensional Fact Model) as a formalism and the intuitive UX of indyco Builder, IT and business people can sit together and make sense of their data model without having in mind implementation details or constraints. Unleashing the potential of conformed hierarchies, for example, helps your company to cross the information silos defining a common background for your Enterprise Data Warehouse.
The good news about using the DFM is that it is an internationally-recognised system of rules developed in 10+ years in both university and real life apps environments. The even better news is that while you design your model in a free and intuitive way with indyco Builder, the rules run in the background, gently suggesting how to evolve your design to be sure it is done right from the beginning. Metrics are calculated in real time as an add-on help to meet quality standards inside your team or enterprise.
Is your company struggling with the meaning of KPIs ordimensions? Is your team struggling to answer two apparently easy questions like “Where does this data come from?” or “Who’s the owner of this data?”. Enrich your conceptual models with heterogeneous information that transforms your design into a business glossary.
When it comes to documentation one thing is well known: documentation starts to be old and not useful the very moment in which you are done with it. What if I could align my Data Warehouse design process and my documentation? This magic is called indyco. Don’t even think about your documentation. Regardless of whether it’s detailed or just an overview, generate it with a single click and be sure it’s always in sync. This always happens during the design process: at any given moment you can document what you are doing with no effort at all. And remember that the ultimate documentation is called indyco Explorer!
Each of the Data Warehouse or Business Intelligence Systems have their own grammar and standards. This means that when you have chosen one, you are done for years. It’s called “lock in”. What if you could easily switch from one to another? Maybe just for Tactical Data Mart or for some R&D that your Data Scientist wants to do. Design your Data Warehouse using a conceptual model, the DFM, and let indyco generate the proper script for your target database: one single source of knowledge, different targets. Easy!
Start your top-down analysis from an aggregated view of a sample DWH, moving your mouse on the area you want to explore and finding out how is connected to other company informations.