How to Optimize Supply Chain Using SQL and Big Data!

SQL and Big Data

A well-optimized supply chain can deliver a wealth of benefits to businesses, and achieving this is easier when you turn to tech solutions designed to process large volumes of data through SQL and Big Data.

Those that have yet to adopt SQL databases and associated big data services may need to be convinced of their effectiveness and impact, particularly in a supply chain context.

To that end, let’s go through some of the ways you can achieve optimization with modern information handling products for SQL and Big Data.

Data unification unlocks actionable insights

In the past, decision-making relation to supply chain issues was a challenge. The amount of data required to form intelligent conclusions, as well as the variety of sources involved, meant lots of companies were left in the dark.

SQL databases solve this by allowing you to draw in data from a raft of sources, both internal and external in origin.

This is where SSIS comes into play. SQL Server Integration Service is a component of Microsoft’s SQL Server database software that can be used to execute a wide range of data migration tasks, and you can get started with this SSIS tutorial to appreciate its full potential.

But what if the data you are dealing with is not appropriate for the standard SQL database environment? For example, you might want to analyze data of wildly different types.

In this case, full-blown big data tools will be more suitable. While SQL solutions are best for structured data, big data tools go beyond this to encompass unstructured data as well.

Analysis of varied data at high speeds and with exceptional precision, backed up by machine learning, means you can unify this process and extract insights which can be relied upon to point you towards supply chain optimizations.

Enhanced forecasting abilities reduce loses

The supply chain is subject to all sorts of pressures over the course of the year, and businesses need to match the ebb and flow of demand without over-provisioning or under-ordering.

This is easier said than done, and prior to the rise of modern data storage and analysis solutions, smaller firms in particular were more vulnerable to unexpected fluctuations.

Big data tools ride to the rescue here as well, empowering you with the means to accurately predict when demand will hit its peak, and when it will subside. Tailoring your supply to follow this trajectory over time will be a breeze.

The aforementioned application of machine learning to data processing also means that you will get better at forecasting demand with each passing year. So the advantages of big data and the technologies like SQL which underpin it will only increase, making early adoption advisable. All students can get SQL homework help online if they struggle with logistics and supply chain management assignments.

Collaboration with supply chain partners improves efficiency

The supply chain is appropriately named, since it is made up of lots of individual links which have to work well together in order to keep the whole structure in one piece.

This means that collaborating with partner firms is a necessary part of the process, and one which can be dealt with more efficiently thanks to big data tools.

Once again this comes down to data unification, but on a much larger scale than was feasible in earlier periods.

Every organization, from the businesses sourcing the materials, to the manufacturers putting them together, to the retail outlets selling them and trucking companies, can be connected to the same data ecosystem.

This enables collaboration across supply chain strategy, sharing of demand forecasting, collective work on customer research, amelioration of logistics and much more besides.

Feeding data into a central pool where cutting edge software can analyze it, and the insights can be distributed and interpreted by all also helps avoid confusion and conflict between links in the supply chain. So a happier, more harmonious and of course eminently profitable infrastructure will emerge as a result.

Automation accelerates decision-making

We have touched on how SQL and big data tools can speed up the extrapolation of insights from the information you have to hand. It is worth exploring the role that automation plays in making this possible.

Because these platforms are able to analyze vast oceans of data under their own steam, this also means that alerts can be issued whenever a particularly important revelation is arrived at.

In turn, this makes the entire supply chain more agile, able to respond to issues and obstacles on the fly, rather than being struck down by them without warning.

Last words

Optimizing your supply chain is undoubtedly simpler with the latest data solutions on your side, but that does not mean it is a complete cake walk.

You will need to familiarize yourself with the tools in this space, or outsource this to a third party that can take the reins for you.

Whatever route you take, know that optimizations are out there waiting for you, and big data gives you the chance to grab them.

SQL and Big Data article and permission to publish here provided by Cristina Par. Originally written for Supply Chain Game Changer and published on December 23, 2021.