Do you know which process manufacturing lines have in common?
Manufacturing lines require high-quality material that’s ready to be used in production. The process they have in common, then, is preparing raw material to make it suitable for value-added production.
This analogy applies to data analytics as well.
Imagine data analytics platforms as manufacturing lines. In this case, the raw material would be the high-quality data required to churn out the right products, which, for us, is actionable analytics.
Raw data can’t be ingested directly on the analytics platform, however, as it may contain errors and discrepancies.
Raw data needs to be cleaned and enriched in a process known as data preparation. According to Forbes, data scientists spend more than 76% of their time preparing and organising data using a variety of tools.
While there are many data preparation solutions out there, the SAS data preparation platform remains one of the most popular options.
In this post, we explore how SAS’s data preparation platform can optimise data analytics platforms to produce high-quality, actionable insights.
Modern businesses collect vast amounts of data every single day. According to recent findings, organisations now collect more data in a single month than they did in the entire decade between 2002-2012.
This data needs to be enriched using data preparation techniques such as wrangling, cleaning, correlation and formatting. Without these processes, analytics platforms can’t produce accurate and actionable insights as the raw data can generate errors and discrepancies in the process.
That said, traditional data preparation techniques can only process less than 10% of the collected data, which means 90% of the raw data is either wasted or takes an unnecessarily long time to be processed, hampering efficiency and output.
SAS data preparation, however, can generate codes to handle cleaning, wrangling, correlation and formatting automatically, eliminating these challenges from the get-go.
As we’ve already established, raw data can create errors and inaccuracies in the data analytics process if ingested directly.
That said, data prepared through traditional techniques can also create errors in the code, leading to inaccurate insights since traditional methods rely on manual processing, which not only requires a long time to complete but is also subject to human errors.
Modern data preparation tools rely on computer-generated codes that are free of this issue. These codes are designed to better identify anomalies, null values and duplicate entries compared to older techniques.
In recent years, more and more organisations are migrating their assets, processes and analytics infrastructure to the cloud to facilitate a collaborative work environment.
Unfortunately, integrating raw data into the cloud analytics platform is easier said than done, as organisations still need human resources to integrate this data into the cloud analytics environment.
SAS data preparation, however, is designed to be self-serviceable, meaning you don’t need a team of data scientists to carry out this process!
With this platform, organisations can clean, wrangle, structure, and format data from data lakes and enter it into cloud data analytics deployments without much human intervention.
Data analytics platforms are great at arming organisations with the insights they need to make strategic, far-reaching decisions.
That said, analytics platforms are somewhat like manufacturing lines. They can’t produce high-quality insights without data that has been prepared to be ingested.
Fortunately, with SAS data preparation, organisations can enrich vast amounts of data without too much human intervention and feed it into analytics platforms.
Optimise your data analytics deployment with the right data preparation tools today.
SAS data preparation is a platform that can help optimise several stages in data collection and analysis. Despite its importance in analysis, the preparation of data is often plagued with missteps. In fact, research shows that data analysts spend a significant amount of time preparing data rather than actual analysing it. To reduce the amount of time spent on analysis, data analysts need to adapt a platform that can optimise the process. Analysts can make the process leaner, more efficient, and reduce the cost of data collection by adopting SAS data preparation.
Let us take a deep dive into how the platform works.
One reason why data preparation takes a long time is because of data cleaning. It requires a significant amount of time. For most organisations dealing with structured and unstructured data, this can be a nightmare scenario.
However, SAS data preparation can make the process more efficient. The platform comes with several features that optimise data preparation to speed up the process. Prebuilt functions, advanced analytics, data preparation, and data visualisation are all found in the package. The features can optimise data preparation capabilities. This way, analysts spend less time on data preparation and more time on analysis.
Duplicate processes are the bane of any data analyst. Whether they are starting a new project or running updates, analysts often have to repeat certain steps in the data creation process. SAS data preparation can remove some of these duplicate steps. Analysts can use certain resources, like shared work, to remove repeating processes and improve productivity. For example, analysts can save data preparation plans, so they don’t have to start from scratch every few hours.
SAS data preparation allows organisations to reuse preparation technology to improve efficiency.
Data preparation is as much a project management challenge, as it is a technical one. Data analysts often work with professionals from different backgrounds to get the job done. Working with people with different expertise can be a challenging endeavor. However, when the analyst is a consultant working with an internal IT team, it creates an even steeper learning curve. But, SAS data preparation can make the learning curve smoother.
SAS data preparation works by offering several tools to help ease collaboration between all members of the project. Activity feeds can be set to notify teams about updates. Furthermore, analysts can share tasks and reuse them. This will help optimise processes and boost productivity. The tools can improve collaboration and teamwork, making the overall process easier.
Data preparation is a process that requires special skills. This often puts a strain on the overall production process. For example, data analysts need to work with the internal IT team to prepare the data for analysis. However, SAS data preparation goes a long way in optimising the process.
The platform removes the need for coding and SQL. Furthermore, the use of a visual interface makes data preparation much easier. It removes the technical barriers required for data preparation. Besides removing complex technical requirements, SAS data preparation neatly integrates into the reporting and analytics pipeline.
The freedom to work autonomously optimises the data preparation process. This is because there are no specialist skills required to prepare data for data analysis. Instead, this allows data analysts to explore data and prepare it as they see fit. They don’t have to depend on specialist skills, which speeds up the process significantly.
Data collection and analysis is a pivotal step in the overall process. However, it also takes a significant amount of time, taking time away from analysis. SAS data preparation can optimise the data analysis preparation process by a significant margin.
The platform comes with several features needed to optimise data preparation. Some of these features include data visualisation, automation, and management features, all of which can ease communication between different team members. By using SAS data preparation, both analysts and organisations benefit because they can optimise the process to improve the rate of findings and lower operating costs.
As businesses and organisations become increasingly dependent on data and analytics, harnessing the power of all this information is equally important. The problem with this is that many businesses, especially small businesses and organisations, often lack the resources to fully capitalise on their analytics. Recognising the value of a powerful analytics platform is only the first step – the next step is interpreting and leveraging this information effectively. That’s where a platform like SAS Data Preparation comes into play.
With hundreds of pieces of data flowing into an organisation at any given point, many organisations turn to the expertise of skilled analytics, IT, and/or data specialists to help navigate these often tumultuous waters. Similarly, many organisations attempt to train managers and staff to become data-savvy.
Unfortunately, these approaches aren’t always feasible since many organisations simply lack the resources to hire entire teams of IT experts and data specialists who, more often than not, come at a high price. Additionally, internalising data expertise is most definitely not the best option for data trends, applications, and techniques are constantly evolving. This means that an organisation’s staff would have to stay in the loop of things – in addition to the other daily tasks they’re required to perform.
In short, data preparation, management, and monitoring is not easy. SAS Data Preparation is built for instances like this where self-service data preparation is streamlined in such a way that any organisation and its staff members can leverage the power of analytics. In the following sections, we run through four critical ways SAS Data Preparation makes this happen.
One of the biggest knocks on any platform, especially an analytics one, is that it would need to be paired with equally innovative and adaptive personnel capable of organising and interpreting the capture data. Naturally, in most instances, this task would be highly technical and expensive, however, SAS Data Preparation changes this entirely.
With SAS Data Preparation in place, organisations would not need any personnel with specialised skills in coding or SQL to navigate their analytics environment. The software’s visual interface ensures that data preparation is simplified and non-technical users have the ability to blend and shape their data in their own unique ways. Thanks to SAS Data Preparation, an organisation’s staff are empowered with the ability to manage data without the assistance of expert help and IT personnel are now free to focus on more strategic, forward-thinking tasks.
This is already implied in the application’s name but SAS Data Preparation’s ability to minimise the time a data analyst spends on preparing data is undeniably commendable. Thanks in no small part to the system’s prebuilt transformations and cleaning functions that operate in-memory, the processing speed of data preparation is unparalleled. Additionally, the systems facilitates an environment where advanced analytics, data visualisation, and data preparation capabilities are all seamlessly combined.
Faster data preparation means analysts and data users have significantly more time to spend on exploring the data and deriving the key insights they are after in near-real time.
Duplication is quite likely the antithesis of efficiency. It also takes place far more often than is ideal, which can be a real back-breaker for an organisation. Fortunately, with SAS Data Preparation, whether you need to share code with your IT department or any other group/individual, the system lets you do this.
You can share your automatically generated code with your organisation’s IT department to make sure it is run during every source data update- guaranteeing across-the-board centralisation and no duplication. Thanks to SAS Data Preparation, many organisations have transformed their operations from one that was centered on the work of decentralised silos to one that is now an integrated environment of shared work/resources.
While we are on the topic of collaboration, it’s important to highlight how SAS Data Preparation contributes in this area as well. Given that many organisations are project-based entities, it should come as no surprise that collaboration between team members is vital. Through SAS Data Preparation, individual team members can share jobs as centrally managed assets, track progress via project activity feeds that can have tasks added, posts updated, and notifications sent out to other team members.
Collaboration is at the heart of SAS Data Preparation – working together and sharing tasks has never been easier!
As official SAS Resell Partners, SAS Data Preparation is one of the many SAS softwares we provide to many of our customers, in addition to our installation, administration, and hosting services. Feel free to contact us if you’d like more information and we’d be happy to answer any questions you may have. In the meantime, be sure to stay tuned to this feed for the latest SAS and analytics-related news!