Is Your Data Out Of Control?
Aptude’s Proven Data Science & Analytics Program Gives You Data You Can Trust
Do you need to create new data reports and visualizations on-demand? Perhaps you’d like to use your historical data to make dynamic, real-time decisions using AI and ML? Even moving from a data lake to a data warehouse will enable your business to do so much more. Once you have a data warehouse, you can utilize visualizations tools like Excel, Tableau or PowerBI. With structured data pipelines, you can begin slicing data in new ways. Once you know your data is relevant, correct and secure, you can trust it to make data-driven decisions that will impact the success of your corporation.
Whatever form of digital transformation your company needs, there’s a good chance that it will require some work. Aptude can help get your data under control.
Twelve Data Problems Commonly Faced by Blue-Chip Companies
Siloed Data
Data held by one group or business unit that isn’t shared by others
Poor Data Quality
Issues with data completeness or accuracy
Data Deluge
Too much data, especially unstructured data, resulting in data pools and data lakes
Data Duplication
Excessive copies of data that decreases storage capacity
Lack of Data Expertise
Having a team which can’t implement data engineering, predictive analytics, machine learning, or big data solutions
Improper Data Linking
Lack of an ability to connect different data sets together to perform semantic queries OR data is improperly linked and thus less valid for decision-making
Data Entry Errors
Errors that are caused at the point of entry; can be transcription or transposition errors
Lack of Data Transparency
An inability to easily access and work with data no matter their location or application source
Cross-Team Misalignment
When your teams have different procedures, goals, and standards about data
Lack of Data Consistency
Lack of consistency in measurement of variables throughout the datasets
Lack of Visualization
Inability to tell data-driven stories or glean fast insights from data
Privacy Concerns
When data stored isn’t secure or compliant with privacy laws and regulations
What’s Possible When You Mix the Right Components to Solve Core Data Problems?
That’s Where Our Periodic Table of Data Science Comes Into Play…
Data Engineering
Our Data Practice which focuses on preparing data so it can be used in data analytics, data visualization, or data science
Data Architecture
Experienced Guidance in how data is collected, arranged, integrated, and put to use in data systems and in organizations
ETL Processes
Extract, transform, load data from one database to another (usually, a data warehouse)
Data Visualization
Charts, graphs, maps, and dashboards that provide an accessible way to see and understand trends, outliers, and patterns in data
Machine Learning
Computer algorithms that improve automatically through “learning”
Big Data
Large volumes of data, both structured and unstructured
Artificial Intelligence
Algorithms designed to make decisions, often using real-time data
Predictive Analytics
Analyze current and historical facts to make predictions about future or otherwise unknown events
Deep Learning
A facet of machine learning based on artificial neural networks with representation learning
Natural Language Processing
A mix of linguistics, computer science, and artificial intelligence concerned with how to program computers to process and analyze large amounts of natural language data
Data Warehousing
Central repositories of integrated data from one or more disparate sources
Data Pipelines
Consolidate data from multiple sources and make it available for analysis and visualization
Database Management
Store, retrieve, define, and manage data in a database
Technical Project Management
Expert Program, Portfolio, and Project Leadership of your data projects
PowerBI
Microsoft data visualization and dashboarding tool
Tableau
Industry-leading data visualization tool
Smartsheet
Technical project management using Smartsheet
Excel
Powerful Microsoft spreadsheet tool
Hadoop
A robust Big Data programming framework
Python
Our preferred Programming Language for Data Science Projects
Structured Query Language
Programming language to manipulate data in your databases
Believe in Data Science
Aptude’s 20+ years of data experience gives you relief from data obstacles that limit your digital transformation.
Aptude is a leading provider of data science services, in no small part because of our growing Python Center of Excellence in Mexico City. Our robust data practice includes over 19 different data solutions and skillsets to help you get control of your data and begin making data-driven decisions faster than ever before.
Don’t Tackle Your Deluge of Data on Your Own. Aptude Can Help.
With Aptude leading your next data project, you’ll be able to…
• Avoid mistakes. We’ll help you avoid falling into common, easily-avoidable missteps that an expert team will have seen (and solved) before
• Solve the right problem. Get an expert outside eye on your situation, root causes of data problems, and potential solutions
• Explore a range of data-driven solutions. Rather than the solution you think you’ll need; we’ll quote you what we know you’ll need to keep moving forward based on our years of proven domain experience
• Get dynamic resourcing. Get expert onshore help for the “build phase”, and more affordable offshore or nearshore help for the “run phase”. Or whatever mix fits your needs.
• See cost savings. Our AptudeFlex model lets you get more done than you would have hiring full-time data staff who can each only do a limited set of work.
• Get Leadership from Day 1. Our team members (especially our team leads) each have years of domain experience. Which means we’re not just doers – we’re leaders.
The fastest way to get started is to fill out the form on this page to request more information.
We’ll follow up with a mutual NDA, and then begin the conversation about your requirements, goals, and needs. Finally, we’ll work together to design an expert staffing or consultative solution that fits your needs and your budget. Once you’re ready, we’ll move forward.
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