Jun 19, 2020

Where Are the Data Science Agencies? Right Here in Pittsburgh!

The truth is in the data. Now more than ever before, data is being collected, scrubbed, and analyzed in order to save businesses money and find innovative ways to increase their efficiency. When companies take a hard look at what their numbers show, it can offer them insightful clues as to where they can be more effective in whatever it is they’re trying to do--whether that’s increase revenue, become more cost-efficient, or improve and streamline processes.

Although data science has been around for years, it has recently gained a lot of attention, and it seems that everyone wants data--from giant companies such as Facebook, all the way down to Pittsburgh small businesses. But what exactly is data science and how could a Pittsburgh data science agency help your company?

In this article, we’ll examine:

Why data is so important
The many uses of data
List of Pittsburgh data science agencies

Data science agencies use tools to help their clients make better business decisions. Image courtesy of Dataquest.

What Exactly is Data Science and Why is it So Important?

Everyone wants to get their hands on the data!

Broadly, data science refers to the process that utilizes tools, algorithms, and machine learning techniques to decipher patterns--based on the history and performance of these patterns allows you to make predictions about the future. These patterns can then be analyzed to see if there is any useful information that a company might want to explore further. Data can be used to make prescriptive assessments of the future--influencing decisions made today. This is extremely important to companies in all kinds of industries--it gives them a way to “see” into the future. By analyzing patterns, they can start to make much more informed decisions that can have a positive effect on their growth.

Not that long ago it was difficult to manage and store data--a lot of the time data was stored in separate silos where access was difficult or limited. The separation into silos meant that anyone who was looking at the data was not getting the entire picture either. This made it cumbersome to try and glean any sort of useful information from data in disparate locations. Now that there are much easier ways to store and access data, it’s almost a no-brainer for companies to either keep it in-house, or have a data management firm store their data.

Data science helps businesses create models that will allow them to get full use out of their data. Here are three major ways:

Predictive analytics. This type of model allows businesses to use their data to see how likely an outcome is going to happen in the future. If you see that your customers are more likely to buy items when there is a 50% off sale then when there isn’t one, then this model can help you determine how often to have a sale.
Prescriptive analytics. The next step up is a model that will use the patterns found in the past and use it to provide advice based on different variables. A great example of this is a self-driving car, which uses all the information it gathers to decide when is the appropriate time to turn, stop, slow down, etc. based on past patterns.
Machine learning. This model can be used for both for making predictions and pattern discovery. Depending on your needs, you can program an algorithm to make predictions based on certain criteria, or you can allow the algorithm to learn and discover patterns as it goes through the data.

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Analysis of data can help companies develop better business strategies and give them a competitive edge. Image courtesy of Towards Data Science.

How Can Data be Used?

Data analysis

So now that you have all this data stored away, how exactly should you be using it? As we touched on briefly above, data needs to be analyzed and assessed in order for it to be useful--raw data is just that, raw. Data analysis is how companies find out what it is they can learn from their data, especially how they can make their businesses better and more competitive. However, before you start analyzing data, you have to ensure that the data is “clean” and not “dirty.” Dirty data refers to the kind of data that is inaccurate, incomplete, or inconsistent. If you do not first scrub your data for these problems, there’s no way you’ll be getting the results you’re looking for.

Depending on what you want to decipher from your data, having inaccuracies and missing information can add up, which is why companies should undergo a thorough clean up by a data science agency or data analysis firm. They’ll help to fill in the holes where there’s missing information, or eliminate duplicates that can change or skew the results of your analysis.

Once your data is clean, using computer languages such as SQL or Python you can begin to ask the right questions. Depending on whether you question the data to look for ways to increase sales, lower costs, or cut down on fraud, you’ll have to begin by asking the right questions. This does take expertise, since the data must be manipulated into a usable action or conclusion that a company can reasonably undertake.

Experimentation

Data is also used by companies who are searching for a way to make their business better and more profitable. They use data to segment out and test new designs and strategies on their users. Although companies have always tried new ways to increase customer engagement or ways to get more sales, now they can use their data to see what is more likely to draw traffic to their site, increase customers purchase amounts, or customize outreach to increase brand loyalty and engagement. Data can offer them possibilities most likely to succeed, and after trying out a few, businesses can gauge what works and what doesn’t.

Machine learning

Machine learning models set up by data scientists allow AI to learn from the pattern in the data. When machines are programmed to understand, replicate, or even develop a process, they are using the data collected to do so. Drawing on what they’ve either been programmed to do specifically--or actually learning from the data-- will create conclusions that can assist the company with decisions and decide what direction to go in.

Consider contacting one of these data agencies to help your business thrive!

Pittsburgh’s Data Science Agencies

A non-exhaustive list of data science agencies right here in Pittsburgh

MobiWeb

About: Innovating new ways of doing business and experimenting with emerging technologies and business models.

# of Employees: Freelance with offices in Pittsburgh

Services Offered: Big data, CMS development, digital marketing, open source, Python, mobile application, JS and PHP frameworks

Key Clients: Fanbash, Classic Catering, Calypso, Cartalyst Solutions

mobiwebtech.com | @mobiwebtech | linkedin.com/company/mobiweb-technologies

UXAX

About: Data firm that helps clients discover analytics best practices to get a better user experience and increase revenue

# of Employees: 2-9

Services Offered: Audit, data quality, data analysis, user experience, artificial intelligence

Key Clients: Morphe Brushes, Brushee

uxax.org | @letsuxax | linkedin.com/company/uxax

JP Enterprises

About: Agency that offers customers digital marketing solutions and data analysis for an increased return on investment

# of Employees: 10-49

Services Offered: Design structure, data governance, data modeling and standardization, content authority and maintenance, product, page, and publication template creation

Key Clients: Black Box, Kennametal, Henry Schein Animal Health, Fisher Scientific

jpenterprises.com | @jpenterprisesunlimitedllc | linkedin.com/company/jp-enterprises

GRWTHCO

About: Helps clients grow their revenue through data driven digital marketing campaigns

# of Employees: 2-9

Services Offered: Data analysis, marketing strategy, website development, social media marketing, audits, search engine marketing

Key Clients: InfoScout, Hacksmith Labs

grwthco.com | @grwthco | linkedin.com/company/grwthco

Management Science Associates

About: Information management company that gives clients the competitive edge in data management, data analytics, and technology

# of Employees: 850-1,000

Services Offered: Information management solutions, business analysis, information technology systems and services, data center management

Key Clients: clients in the life sciences, metals and manufacturing, gaming, and government

msa.com | linkedin.com/company/management-science-associates

Data Ideology

About: Consulting organization that focuses their clients’ people, processes, data, and technology to get more value out of their data analytics investment

# of Employees: 10-49

Services Offered: Data management, data analysis, business intelligence

dataideology.com | linkedin.com/company/data-ideology-llc

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Ciber Global

About: Business solutions agency that helps clients strategize and more forward using data management and technology

# of Employees: 5,000-10,000

Services Offered: Artificial intelligence, data and analytics, application development and management, marketing technology, IT project management

Key Clients: clients in healthcare, hospitality, finance, manufacturing and distribution

ciber.com | @ciber | www.linkedin.com/company/ciber