Data Analytics

You Know You’re a “Citizen” Data Scientist If …

Actian Corporation

June 10, 2022

Data scientist hands typing on laptop with digital artwork

Data collection and analysis have become increasingly important as multiple industries continue to drive their digital transformation initiatives. Whether it’s to improve customer experience, target marketing efforts, or just better understand how their business is performing, data is at the heart of it all.

However, to make data work for you, you need the right people using it. This is where citizen data scientists come in.

What is a Citizen Data Scientist, and What Do They Do?

A citizen data scientist is generally a departmental knowledge worker who may lack formal data science training but possesses skills to leverage data for insights used to solve problems. They are often the bridge between the data experts, IT, and the business and rely on tools that give some measure of abstraction to get data used to make business decisions.

Citizen data scientists can come from just about any area of the organization but typically have a more advanced grasp on how to access and format data from the systems they use. What sets them apart from other data professionals is their ability to work with different teams across an organization to get things done.

They are often described as “data-driven” because they understand how data can improve business outcomes and use this knowledge to influence decision-making across the organization.

How Does a Citizen Data Scientist Differ From Other Data Roles?

While a citizen data scientist shares some similarities with other data roles, there are also some key differences. For one, a citizen data scientist is typically more focused on departmental data and how data is aggregated and formatted to get more complete views of individual issues. They work to ensure that data is being collected effectively and efficiently so that it can be used to its full potential.

In contrast, data scientists as a discipline are more focused on analyzing data and often work with large datasets to find trends and insights.

They often use data to explore hypotheses and uncover trends or opportunities that might be used to aid in large-scale transformative data projects.

So, while there is some overlap between these roles, each one has a distinct focus and skill set, and both provide tremendous value.

What Skills Does a Citizen Data Scientist Need?

Given their focus on ‘for purpose’ data and real-time analytics, citizen data scientists need a strong understanding of how the systems that they are pulling data from and how to normalize that data. This includes everything from data collection to formatting, transformation, and often reporting.

They should be well-versed in SQL (structured query language) as this coding language is often used to interact with databases. Furthermore, they should have experience working with BI tools.

In addition to these technical skills, citizen data scientists need to be good at problem-solving and working with different teams. They should be able to quickly understand the questions being asked and how to get to the right data to answer these questions.

How Are Citizen Data Scientists Changing the Data Landscape?

As the needs of modern businesses continue to evolve, so does the role of the data professional. In today’s data-driven landscape, organizations are looking for data professionals who can build and maintain complex data pipelines and provide real-time insights that can help inform strategic decision-making. However, these experts and teams may also require lead times that can come at a cost when looking to answer less complex problems. This is where citizen data scientists come in.

With their unique skill set and ability to work with different teams, citizen data scientists are well-positioned to help organizations make the most of their data. As data becomes increasingly important to businesses, we can expect to see more roles evolving into citizen data scientists to help them navigate the ever-changing data landscape and get answers more quickly.

Conclusion

The importance for organizations to better understand and utilize data has never been greater. While traditional roles in data analytics and data engineering are still critical, there is a growing need for data professionals who can bridge the gap between these two disciplines. Citizen data scientists will continue to play an essential role in helping organizations fully unlock the value of their data while ensuring they remain competitive and viable in today’s quickly shifting digital landscape.

About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.

Data Intelligence

What are the Benefits of Big Data in the Retail Industry?

Actian Corporation

June 6, 2022

The recent COVID-19 crisis has forced retail players to reinvent themselves and accelerate their digital transformation. To gain a competitive advantage, the retail industry must rely on Big Data. Personalized experiences, optimized pricing, supply-chain connectivity; discover how data has transformed the retail & e-commerce sector.

Figures from the FEVAD (Federation of e-commerce and distance selling) indicate that the e-commerce sector has exceeded 129 billion euros in 2021, up 15.1% since 2020. The increasing success of online vendors has attracted more and more historical retailers to launch their e-commerce adventures. The consequence? The line between e-retail and retail is becoming increasingly tenuous. According to the LSA/HiPay 2021 study, 63% of French shoppers say they have used click & collect at least once, 44% have had a product delivered to their home, and 37% have returned a product purchased online.

In this very competitive context, the use of Big Data, driven by Artificial Intelligence and Machine Learning, has many advantages for this industry.

Benefit 1: A 360° View of Customers

Faced with an increasing amount of digital and omnichannel consumers, retail players can have a 360° view of their customers through data. Indeed, data plays a huge role in building a relationship between customers and the retailer by providing point-of-sale experts with in-depth knowledge about a customer or a product. With a better understanding of the customers, their habits and expectations, as well as the products that are sold, salespeople can have richer and more satisfying jobs. An advantage that can be seen as a response to the talent shortage affecting the industry.

But that’s not all. By using purchase records from a large portfolio of customers, retailers can use predictive analysis to adapt their offers in real-time. For example, companies can define specific personas or offer personalized discounts.

Benefit 2: Optimize Pricing

The analysis of supply and demand is a must for any business. In a hyper-competitive context, with tense consumer purchasing power, selling at the right price is an absolute necessity. One of the main guarantees of the use of data to optimize pricing is to preserve the attractiveness of the brand while protecting its margins.

This is even more critical for multi-site brands, spread over a vast territory. They must not only adapt their pricing based on customer expectations and behavior, but also to the competition in a given area – two major strategic levers for the retail industry.

Benefit 3: Innovate to Improve Products & Services

Under the effect of digitalization, consumer habits are evolving at a very fast pace. Brands must therefore constantly innovate. But innovating can be a risky and expensive process.

With data, retail players can rely on the knowledge they have on their customers’ preferences and expectations to define the roadmap for innovating their products and services. The challenge? Winning the race to constantly conquer new markets, while keeping the R&D budgets under control.

Benefit 4: Offer Personalized Shopping Experiences

Since the beginning of the COVID-19 crisis, the explosion of online shopping has attracted a population that used to shop in physical stores. To differentiate themselves, retail players must do everything they can to offer personalized shopping experiences.

Data is the basis of all personalization, especially for retailers who have embarked on the path of e-commerce. The ambition? To exploit the knowledge of on and off-line customers to harmonize experiences. Optimized and controlled data allows retailers to take advantage of the benefits of digital platforms while reinforcing the quality of in-store contact.

Benefit 5: Fluidify the Supply-Chain

One of the reasons why customers will visit a physical store rather than purchase a product online is to make physical contact with the said-product. In fashion for example, trying on a piece of clothing almost always makes the difference. In addition, having the possibility of leaving with one’s purchase without shipping delays is one of the most important factors for purchasing in a physical store.

Optimized inventory management, fluidity of supplies, control of logistics costs… It is crucial to ensure the excellence of data in order to guarantee the availability of products at the point of sale.

About Actian Corporation

Data Management

Technical Trifecta: The Future of Data Professionals

Actian Corporation

June 3, 2022

Group of data professionals reviewing information in a digital environment

Data-driven roles are in demand. According to research firm Deloitte, the number of postings for positions in data science, data engineering, machine learning (ML), and visualization now surpasses those for more familiar skill sets such as customer service, marketing, and public relations (PR).

For database administrators (DBAs), business technologists, and data engineers, this increasing demand comes with the opportunity to explore new roles within their organization and expand existing skill sets to make better use of emerging technologies.

But what comes next? Beyond the growing need for skilled data staff, what does the future hold for this trifecta of technology professionals? How will these roles evolve over the next few years to align with the growing impact of cloud technologies, Internet of Things (IoT) deployments, and the increasing use of artificial intelligence (AI) and machine learning (ML) frameworks?

The Database Administrator: Delivering Dynamic Architecture

DBAs are responsible for managing, monitoring, and upkeep of SQL, NoSQL, Oracle, and other database environments. The advent of process automation and machine learning tools, however, has led to questions about the future of this role: If software tools can handle most of the heavy lifting when it comes to repetitive and error-prone tasks, where does that leave DBAs?

Moving forward, database administrators should expect a shift in priorities that sees them focusing on the dynamic nature of database architecting, capacity planning, and scaling to help businesses reliably access and leverage data across multiple clouds and on-premises instances. Put simply, the role of DBAs is shifting away from managing databases to assisting organizations in making the most of evolving and interconnected database architecture.

The Data Engineer: Abstracting the Source

Data engineers leverage their expertise to discover trends and develop new algorithms that help companies pinpoint actionable information within data sets. Historically, data sources defined the scope of this work—each unique source required its own set of processes and algorithms to facilitate effective data capture.

Consider user data stored across different databases. While the underlying asset—the user—remains the same in each case, disparate data sources meant different analysis models for each. Once extracted and formatted, data from different sets could then be combined to facilitate trend analysis and strategic decision-making.

The future of data engineering, however, is about abstracting the source. By leveraging both machine learning algorithms and AI frameworks, new engineering approaches are capable of capturing and understanding data in a way that’s set- and source-agnostic.

The Business Technologist: Finding Common Ground

Business technologists often have a combination of operations and development skills—for example, they may be data analytics experts who also have experience designing and building applications. This diversified expertise empowers technologists to help improve communication and collaboration across multiple departments. By functioning outside the traditional paradigm of IT, business technologists are better equipped to see the bigger picture and identify opportunities for increased efficiency.

The ongoing integration of IT into business processes at scale, however, sets the stage for an evolution of the business technologist role that broadens their communications strategy. This starts with the C-suite. To secure executive support and ensure appropriate funding for new IT projects, business technologies must now bridge the gap between technical and tactical communication to capture C-suite attention and encourage specific action.

There’s also a growing need for business technologists to cultivate connections with outside experts such as managed service providers. From data backup and disaster recovery solutions to on-demand data management platforms, there are now a host of solutions that can make business operations easier—if companies can pinpoint where they’re best used and how they can integrate with current operations.

The Evolving Future of Data Expertise

In the near term, data professionals will see increasing demand for their skills as businesses look to effectively leverage the volume, variety, and velocity of information produced across their networks.

Over the next few years, however, members of this technology trifecta should expect changes in their roles as technology continues to evolve. For DBAs, this means a move away from static management and monitoring to dynamic architecting and scaling. For data engineering staff, a shift to source-agnostic data analysis is on the horizon. And for business technologists, communication is key—not just across departments but outside traditional boundaries to leverage the potential of provider-driven expertise.

About Actian Corporation

Data Platform

The Customer Journey and the Role of Data

Jennifer Jackson

May 23, 2022

A typical buyer’s journey moves through distinct phases starting with Awareness, continuing on to Consideration, Purchase, and Onboarding/Post-Purchase, and hopefully ending in Advocacy. Much of the journey is carried out digitally – up to 67%, according to some estimates. Data breadcrumbs are left behind along a digital path, as people search online, sign up for activities, open emails, buy products, and post reviews. Each of these signals tells a story.

But how can marketers make sense of the story? That takes skill – and a helping hand from modern technology.

First, marketers do what they can to encourage customers to keep moving forward. They do this by feeding the types of content customers crave based on where they are in their journey. Each interaction gives marketers a chance to collect and interpret the digital signals – and the more signals, the better. As they pull mounds of data from all the different channels, apps, and information sources, marketers consolidate it into a single profile – often referred to as a 360-degree view of the customer. Once the resulting event table is established, organizations can respond more strategically with the appropriate message at the appropriate time in the right channel.

A Data Platform for a 360-Degree Customer Journey

A data platform integrates data from all sources and puts it in one place. This allows analysts to explore what’s there to ferret out patterns and trends. The insights generated can be put to good use, such as predicting buyer behavior, preventing churn, or recommending meaningful offers. This turns a run-of-the-mill customer experience into a positive engagement, personalized for each buyer’s journey.

Still, a data platform doesn’t just enable a 360-degree view – it opens up a whole new landscape for marketers. While customer data platforms, or CDPs, offer a view of the customer, a data platform like Actian gives you so much more. The same people, the same investment, the same data, and the same processes can be used to analyze other sets of data. This allows marketers to review other types of data – everything from financial to supply chain to support – and use it to enhance the customer experience.

The Actian Data Platform helps companies understand where customers are, and where they’re going. Using sophisticated analytics, companies can better interpret customer sentiment and intent when interacting with your brand and/or products, which can also be a valuable asset for other parts of the organization. Better insights can fuel product and service development, improve customer service, and make financial planning more efficient.

At Actian, we’re focused squarely on customer experience. We provide that integrated, 360-degree view that enables you to know your customers and respond to them in the most strategic way possible. With Actian Data Platform, you not only understand the customer journey, you make it memorable.

About Jennifer Jackson

Jennifer"JJ" Jackson is CMO of Actian, leading global marketing strategy with a data-driven approach. With 25 years of branding and digital marketing experience and a background in chemical engineering, JJ understands the power of analytics from both a user and marketer perspective. She's spearheaded SaaS transitions, partner ecosystem expansions, and web modernization efforts at companies like Teradata. On the Actian blog, she discusses brand strategy, digital transformation, and customer experience. Explore her recent articles for real-world lessons in data-driven marketing.

Data Intelligence

What is Data Profiling?

Actian Corporation

May 8, 2022

Businesswoman Looking At Contract Form Through Magnifying Glass

The purpose of any data project is to transform available data into valuable assets that will put your company on the path to excellence. To achieve this, data must be easy to discover and catalog. The objective is to make it not only accessible but above all understandable and exploitable for your employees who use it daily. One of the levers to achieve this is Data Profiling. Here are some explanations.

The very principle of a data strategy is to give your teams the means to rely on tangible, representative, and quality information to fulfill their missions. But raw data is not enough. Like a precious mineral, data must be methodically refined. One of the essential phases of making data speak is called Data Profiling. It is a process that relies on analyzing and exploring the available data to understand:

How they are structured.
The information it contains.
The relationships between different datasets.
How they could be associated, combined, and used more efficiently.

What are the Different Types of Data Profiling?

When you launch a data profiling process, you examine and analyze all of your data assets to determine their structure, nature, and possible combinations. In this way, you can identify the interdependencies between datasets to better make them talk. According to data experts, there are three types of Data Profiling: structure profiling, content profiling, and relationship profiling.

Structure Discovery

One of the key elements of data exploitation is its optimal organization. To do this, you need to look at the structures of the data. Structure profiling is the type of Data Profiling that ensures that the data is correctly formatted and consistent within a database. Structure Discovery or “structure profiling”, refers to a process of validating the format and consistency between datasets.

Content Discovery

Content discovery, or content profiling, is based on the analysis of rows of data to identify errors and systemic problems. For example, the most common use is to examine a list of customers to identify those with invalid email addresses. The goal is to highlight null or erroneous values so that they can be corrected as soon as possible.

Relationship Discovery

The third type of data profiling, called relationship discovery, is used to analyze and identify the relationships of data used between spreadsheets or database tables. To do this, you will need to perform a metadata analysis to detect possible connections between different data sources and identify overlaps.

The Benefits of Data Profiling

There are three main benefits of Data Profiling. The first is that it saves time before launching a data project. You can take an exploratory approach to determine whether the data you have will really enable you to gain the knowledge you need. Then, and only then, can you implement your project.

The second benefit of Data Profiling is that it improves data quality. Data Profiling ensures that your data is clean, accurate, and ready to be distributed throughout the organization.

Finally, Data Profiling allows you to expand the scope of what is possible. Your employees need to quickly and easily find specific types of data that can help them launch new projects or capture new markets. When data is not searchable, it can be difficult to locate it in a longer chain. With Data Profiling, data is better identified, categorized, and sorted. Your teams can then easily manipulate it and assemble it into databases using specific keywords.

By engaging in Data Profiling, you create the conditions for optimized exploitation of your data. Done methodically, Data Profiling is a promise of efficiency, relevance, and cost optimization, as it will allow your teams to save precious time and rationalize the exploitation of your data.

About Actian Corporation

Actian Life

Welcome to IMPACTIAN!

Rae Coffman-Bueb

May 2, 2022

It’s been said that we’re all living through unprecedented times. That’s why at Actian, we wanted to put a stake in the ground about how important it is for us to make a positive impact, not only for our customers and employees, but for our communities and society at large.

Today, we’re introducing IMPACTIAN, a new program to drive IMPACT at Actian and beyond. With a focus on corporate social responsibility (CSR) and doing good for our communities and society, Actian is kicking off this program by committing to three core areas:

Science, technology, engineering, and mathematics (STEM).
Food insecurity.
Climate and sustainability.

Through our CSR Program, we are excited to offer employees opportunities for donation matching and volunteer time off to support their philanthropic endeavors. We are eager and excited to champion our employees’ passions for helping those in need and supporting our communities. Whether it be $5 or $1,000, we urge all our employees to take advantage of our employee matching program to help us create a lasting impact.

To jump-start IMPACTIAN, Actian is proud to announce that, for the second consecutive year, we have donated a total of $10,000 to Girls Who Code in recognition of Women’s History Month and in alignment with our pillar of commitment to STEM! If you would like to join us in our commitment and are interested in donating to this organization, you can do so here.

Additionally, we have matched over $2,000 in efforts to support Ukraine relief, donating to organizations such as the Red Cross, Nothilfe für die Ukraine, Four Paws, LSVD, World Central Kitchen, and more.

We’re excited about what lies ahead for IMPACTIAN and can’t wait for you to join us on this journey.

Are you ready to make an impact on the world and change the face of data management and integration? Join our team of enthusiastic, talented minds in a diverse, collaborative environment where you can thrive and grow. Learn more about our career openings at https://www.actian.com/company/careers/.

About Rae Coffman-Bueb

Rae Coffman-Bueb is Director of Employee Experience at Actian, dedicated to enhancing organizational culture. With a background in People Operations, Rae has implemented global best practices that empower teams and streamline HR processes. She provides guidance on talent development, onboarding, and cross-functional collaboration. Rae's blog posts focus on employee engagement, internal communications, and HR innovations. Check them out for tips on boosting workplace satisfaction.

You Know You’re a “Citizen” Data Scientist If …

What is a Citizen Data Scientist, and What Do They Do?

How Does a Citizen Data Scientist Differ From Other Data Roles?

What Skills Does a Citizen Data Scientist Need?

How Are Citizen Data Scientists Changing the Data Landscape?

Conclusion

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What are the Benefits of Big Data in the Retail Industry?

Benefit 1: A 360° View of Customers

Benefit 2: Optimize Pricing

Benefit 3: Innovate to Improve Products & Services

Benefit 4: Offer Personalized Shopping Experiences

Benefit 5: Fluidify the Supply-Chain

About Actian Corporation

Subscribe to the Actian Blog

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Technical Trifecta: The Future of Data Professionals

The Database Administrator: Delivering Dynamic Architecture

The Data Engineer: Abstracting the Source

The Business Technologist: Finding Common Ground

The Evolving Future of Data Expertise

About Actian Corporation

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The Customer Journey and the Role of Data

A Data Platform for a 360-Degree Customer Journey

About Jennifer Jackson

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What is Data Profiling?

What are the Different Types of Data Profiling?

Structure Discovery

Content Discovery

Relationship Discovery

The Benefits of Data Profiling

About Actian Corporation

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Welcome to IMPACTIAN!

About Rae Coffman-Bueb

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